text:
@inproceedings{pappagari_icassp18,
address = {Alberta, Canada},
author = {Pappagari, Raghavendra and Villalba, Jes{\'{u}}s and Dehak, Najim},
booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2018},
file = {:Users/villalba/Documents/Mendeley Desktop/Pappagari, Villalba, Dehak - 2018 - Joint Verification-Identification in End-to-end Multi-scale CNN Framework for Topic Identification.pdf:pdf},
month = {apr},
publisher = {IEEE},
title = {{Joint Verification-Identification in End-to-end Multi-scale CNN Framework for Topic Identification}},
year = {2018}
}
@inproceedings{nidadavolu-is18,
address = {Hyderabad, India},
author = {Nidadavolu, Phani and Lai, Cheng-i and Villalba, Jes{\'{u}}s and Dehak, Najim},
booktitle = {Proceedings of the 19th Annual Conference of the International Speech Communication Association, INTERSPEECH 2018},
doi = {10.21437/Interspeech.2018-2394},
file = {:Users/villalba/Documents/Mendeley Desktop/Nidadavolu et al. - 2018 - Investigation on Bandwidth Extension for Speaker Recognition.pdf:pdf},
month = {sep},
pages = {1111--1115},
title = {{Investigation on Bandwidth Extension for Speaker Recognition}},
url = {http://dx.doi.org/10.21437/Interspeech.2018-2394},
year = {2018}
}
@inproceedings{frederiksen-is18,
address = {Hyderabad, India},
author = {Frederiksen, Peter Sibbern and Villalba, Jes{\'{u}}s and Watanabe, Shinji and Tan, Zheng-hua and Dehak, Najim},
booktitle = {Proceedings of the 19th Annual Conference of the International Speech Communication Association, INTERSPEECH 2018},
doi = {10.21437/Interspeech.2018-2458},
file = {:Users/villalba/Documents/Mendeley Desktop/Frederiksen et al. - 2018 - Effectiveness of Single-Channel BLSTM Enhancement for Language Identification.pdf:pdf},
month = {sep},
pages = {1823----1827},
title = {{Effectiveness of Single-Channel BLSTM Enhancement for Language Identification}},
url = {http://dx.doi.org/10.21437/Interspeech.2018-2458},
year = {2018}
}
@inproceedings{chen-is18,
address = {Hyderabad, India},
author = {Chen, Nanxin and Villalba, Jes{\'{u}}s and Dehak, Najim},
booktitle = {Proceedings of the 19th Annual Conference of the International Speech Communication Association, INTERSPEECH 2018},
doi = {10.21437/Interspeech.2018-2474},
file = {:Users/villalba/Documents/Mendeley Desktop/Chen, Villalba, Dehak - 2018 - An Investigation of Non-linear i-vectors for speaker verification.pdf:pdf},
month = {sep},
pages = {87----91},
title = {{An Investigation of Non-linear i-vectors for speaker verification}},
url = {http://dx.doi.org/10.21437/Interspeech.2018-2474},
year = {2018}
}
@inproceedings{ghahremani-is18,
address = {Hyderabad, India},
author = {Ghahremani, Pegah and Nidadavolu, Phani Sankar and Chen, Nanxin and Villalba, Jes{\'{u}}s and Povey, Daniel and Khudanpur, Sanjeev and Dehak, Najim},
booktitle = {Proceedings of the 19th Annual Conference of the International Speech Communication Association, INTERSPEECH 2018},
doi = {10.21437/Interspeech.2018-2015},
file = {:Users/villalba/Documents/Mendeley Desktop/Ghahremani et al. - 2018 - End-to-End Deep Neural Network Age Estimation.pdf:pdf},
month = {sep},
pages = {277----281},
title = {{End-to-End Deep Neural Network Age Estimation}},
url = {http://dx.doi.org/10.21437/Interspeech.2018-2015},
year = {2018}
}
@inproceedings{sell-is18,
abstract = {We describe in this paper the experiences of the Johns Hop-kins University team during the inaugural DIHARD diarization evaluation. This new task provided microphone recordings in a variety of difficult conditions and challenged researchers to fully consider all speaker activity, without the currently typi-cal practices of unscored collars or ignored overlapping speaker segments. This paper includes details about research decisions made in the process of the evaluation, including explorations of training data, feature bandwidth, speech activity detection, and i-vector versus x-vector representations. The utility of sys-tem fusions and domain-specific processing are also considered. In all cases, deeper analyses are presented using the develop-ment data, for which truth labels were given during the evalu-ation, while evaluation scores are only presented for a subset of the systems. Finally, we discuss lessons learned and remain-ing challenges left for future work within the lens of this new approach to diarization performance measurement.},
address = {Hyderabad, India},
author = {Sell, Gregory and Snyder, David and Mccree, Alan and Garcia-Romero, Daniel and Villalba, Jes{\'{u}}s and Maciejewski, Matthew and Manohar, Vimal and Dehak, Najim and Povey, Daniel and Watanabe, Shinji and Khudanpur, Sanjeev},
booktitle = {Proceedings of the 19th Annual Conference of the International Speech Communication Association, INTERSPEECH 2018},
doi = {10.21437/Interspeech.2018-1893},
file = {:Users/villalba/Documents/Mendeley Desktop/Sell et al. - 2018 - Diarization is Hard Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge.pdf:pdf},
keywords = {Index Terms,speaker diarization},
month = {sep},
pages = {2808----2812},
title = {{Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge}},
url = {http://www.danielpovey.com/files/2018{\_}interspeech{\_}dihard.pdf http://dx.doi.org/10.21437/Interspeech.2018-1893},
year = {2018}
}
@inproceedings{cho-is18,
address = {Hyderabad, India},
author = {Cho, Jaejin and Pappagari, Raghavendra and Kulkarni, Purva and Villalba, Jes{\'{u}}s and Carmiel, Yishay and Dehak, Najim},
booktitle = {Proceedings of the 19th Annual Conference of the International Speech Communication Association, INTERSPEECH 2018},
doi = {10.21437/Interspeech.2018-2466},
file = {:Users/villalba/Documents/Mendeley Desktop/Cho et al. - 2018 - Deep Neural Networks for Emotion Recognition combining audio and transcripts.pdf:pdf},
month = {sep},
pages = {247----251},
title = {{Deep Neural Networks for Emotion Recognition combining audio and transcripts}},
url = {http://dx.doi.org/10.21437/Interspeech.2018-2466},
year = {2018}
}
@inproceedings{richardson18,
address = {Les Sables d'Olonne, France},
author = {Richardson, Fred and Torres-carrasquillo, Pedro A and Borgstrom, Jonas and Sturim, Douglas and Gwon, Youngjune and Villalba, Jes{\'{u}}s and Chen, Nanxin and Trmal, Jan and Chen, Nanxin and Dehak, Najim},
booktitle = {Proceedings of Odyssey 2018 - The Speaker and Language Recognition Workshop},
file = {:Users/villalba/Documents/Mendeley Desktop/Richardson et al. - 2018 - The MIT Lincoln Laboratory JHU EPITA-LSE LRE17 System.pdf:pdf},
month = {jun},
title = {{The MIT Lincoln Laboratory / JHU / EPITA-LSE LRE17 System}},
year = {2018}
}
@inproceedings{villalba-od18,
address = {Les Sables d'Olonne, France},
author = {Villalba, Jes{\'{u}}s and Brummer, Niko and Dehak, Najim},
booktitle = {Proceedings of Odyssey 2018 - The Speaker and Language Recognition Workshop},
file = {:Users/villalba/Documents/Mendeley Desktop//Villalba, Brummer, Dehak - 2018 - End-to-End versus Embedding Neural Networks for Language Recognition in Mismatched Conditions.pdf:pdf},
month = {jun},
title = {{End-to-End versus Embedding Neural Networks for Language Recognition in Mismatched Conditions}},
year = {2018}
}
@inproceedings{chen-icassp18,
address = {Alberta, Canada},
author = {Chen, Nanxin and Villalba, Jes{\'{u}}s and Carmiel, Yishay and Dehak, Najim},
booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2018},
file = {:Users/villalba/Documents/Mendeley Desktop/Chen et al. - 2018 - Measuring Uncertainty in Deep Regressin Models The Case of Age Estimation from Speech.pdf:pdf},
month = {apr},
publisher = {IEEE},
title = {{Measuring Uncertainty in Deep Regressin Models: The Case of Age Estimation from Speech}},
year = {2018}
}
@inproceedings{villalba-is17,
address = {Stockholm, Sweden},
author = {Villalba, Jes{\'{u}}s and Brummer, Niko and Dehak, Najim},
booktitle = {Proceedings of the 18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Brummer, Dehak - 2017 - Tied Variational Autoencoder Backends for i-Vector Speaker Recognition.pdf:pdf},
month = {aug},
publisher = {ISCA},
title = {{Tied Variational Autoencoder Backends for i-Vector Speaker Recognition}},
year = {2017}
}
@inproceedings{moro-maveva17,
address = {Florence, Italy},
author = {Moro-Velazquez, Laureano and Godino-Llorente, Juan I and Gomez-Garcia, Juan A and Villalba, Jes{\'{u}}s and Shattuck-Hufnagel, S and Dehak, Najim},
booktitle = {Proceedings of MAVEBA 2017},
file = {:Users/villalba/Documents/Mendeley Desktop/Moro-Velazquez et al. - 2017 - Use of Acoustic Landmarks and GMM-UBM Blend in the Automatic Detection of Parkinson's Disease.pdf:pdf},
keywords = {acoustic landmarks,gmm -ubm,parkinson,rasta-plp,s disease},
month = {dec},
title = {{Use of Acoustic Landmarks and GMM-UBM Blend in the Automatic Detection of Parkinson's Disease}},
year = {2017}
}
@inproceedings{vinals-ib16,
abstract = {{\textcopyright} Springer International Publishing AG 2016. The goal of this paper is to study the inclusion of deep learning into the diarization task. We propose some novel approaches at the feature extraction stage, substituting the classical usage of short-term features, such as MFCCs and PLPs, by Deep Learning based ones. These new features come from the hidden states at bottleneck layers in neural networks. Trained for ASR tasks. These new features will be included in the University of Zaragoza ViVoLAB speaker diarization system, designed for the Multi-Genre Broadcast (MGB) challenge of the 2015 ASRU Workshop. This system, designed following the i-vector paradigm, uses the input features to segment the input audio and construct one i-vector per segment. These i-vectors will be clustered into speakers according to generative PLDA models. The evaluation for our new approach will be carried out with broadcast audio from the 2015 MGB Challenge.},
address = {Lisbon, Portugal},
author = {Vi{\~{n}}als, Ignacio and Villalba, Jes{\'{u}}s and Ortega, Alfonso and Miguel, Antonio and Lleida, Eduardo},
booktitle = {Proceedings of IberSpeech 2016},
doi = {10.1007/978-3-319-49169-1_27},
file = {:Users/villalba/Documents/Mendeley Desktop//Vi{\~{n}}als et al. - 2016 - Bottleneck Based Front-end for Diarization Systems.pdf:pdf},
isbn = {9783319491684},
issn = {16113349},
keywords = {Bottlenecks,Deep neural networks,Diarization,bottlenecks,deep neural networks,diarization},
month = {nov},
number = {610986},
pages = {276--286},
title = {{Bottleneck Based Front-end for Diarization Systems}},
volume = {10077 LNAI},
year = {2016}
}
@inproceedings{villalba-asru15,
address = {Scottsdale, Arizona, USA},
author = {Villalba, Jes{\'{u}}s and Ortega, Alfonso and Miguel, Antonio and Lleida, Eduardo},
booktitle = {Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba et al. - 2015 - Variational Bayesian PLDA for Speaker Diarization in the MGB Challenge.pdf:pdf},
month = {dec},
publisher = {IEEE},
title = {{Variational Bayesian PLDA for Speaker Diarization in the MGB Challenge}},
year = {2015}
}
@inproceedings{villalba-is15,
address = {Dresden, Germany},
author = {Villalba, Jes{\'{u}}s and Miguel, Antonio and Ortega, Alfonso and Lleida, Eduardo},
booktitle = {Proceedings of the 16th Annual Conference of the International Speech Communication Association, Interspeech 2015},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba et al. - 2015 - Spoofing Detection with DNN and One-class SVM for the ASVspoof 2015 Challenge.pdf:pdf},
issn = {2308-457X},
month = {sep},
pages = {2067--2071},
publisher = {ISCA},
title = {{Spoofing Detection with DNN and One-class SVM for the ASVspoof 2015 Challenge}},
year = {2015}
}
@inproceedings{villalba-icassp14,
address = {Florence, Italy},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Lleida - 2014 - Unsupervised Adaptation of PLDA by Using Variational Bayes Methods.pdf:pdf},
month = {may},
pages = {744--748},
publisher = {IEEE},
title = {{Unsupervised Adaptation of PLDA by Using Variational Bayes Methods}},
year = {2014}
}
@inproceedings{martinez-ibspeech14,
address = {Las Palmas de Gran Canaria, Spain},
author = {Mart{\'{i}}nez, David and Villalba, Jes{\'{u}}s and Lleida, Eduardo and Ortega, Alfonso},
booktitle = {Proceedings of Advances in Speech and Language Technologies for Iberian Languages, IberSpeech 2014},
doi = {10.1007/978-3-319-13623-3_6},
file = {:Users/villalba/Documents/Mendeley Desktop//Mart{\'{i}}nez et al. - 2014 - Accent Modeling for Language Identification.pdf:pdf},
isbn = {978-3-319-13622-6},
issn = {0302-9743},
keywords = {accent modeling,agglomerative hierarchical clustering,ivector,language identification,plda},
month = {nov},
pages = {49--58},
publisher = {Springer International Publishing},
series = {Lecture Notes in Artificial Intelligence},
title = {{Accent Modeling for Language Identification}},
url = {http://link.springer.com/chapter/10.1007/978-3-319-13623-3{\_}6},
year = {2014}
}
@inproceedings{miguel-is14,
abstract = {Factor analysis is a method for embedding high dimensional data into a lower dimensional factor space. When data are multimodal we use mixtures of factor analyzers (MFA), which assume statistically independent samples. In speaker recogni- tion, samples are not independent because they depend on the speaker in the utterance. In joint factor analysis and i-vectors, theMFA latent factors are tied at different levels. For example, they can be tied for a segment to extract utterance level informa- tion. Tied MFA approaches usually present the drawback that computing the exact posterior of the hidden variables (compo- nent responsibilities and latent factors) is unfeasible. For JFA, the preferred approximation consists in computing the respon- sibilities given a speaker independent GMM and they are fixed during the rest of the process. That implies that the estimated responsibilities for a given sample are independent of the rest of the samples of the utterance not taking into account the shared speaker and channel. We present a novel approximation to jointly estimate responsibilities and latent factors based on sam- pling the latent factor space. This model differs from previous ones in the hidden variables and parameter estimation; and like- lihood evaluation. This approach was tested on the RSR2015 database for text-dependent speaker recognition Index},
address = {Singapore},
author = {Miguel, Antonio and Villalba, Jes{\'{u}}s and Ortega, Alfonso and Lleida, Eduardo and Vaquero, Carlos},
booktitle = {Proceedings of the 15th Annual Conference of the International Speech Communication Association, Interspeech 2014},
file = {:Users/villalba/Documents/Mendeley Desktop/Miguel et al. - 2014 - Factor Analysis with Sampling Methods for Text Dependent Speaker Recognition.pdf:pdf},
issn = {2308-457X},
month = {sep},
pages = {1342--1346},
publisher = {ISCA},
title = {{Factor Analysis with Sampling Methods for Text Dependent Speaker Recognition}},
year = {2014}
}
@inproceedings{villalba-ibspeech14,
address = {Las Palmas de Gran Canaria, Spain},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of Advances in Speech and Language Technologies for Iberian Languages, IberSpeech 2014},
doi = {10.1007/978-3-319-13623-3_8},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Lleida - 2014 - Unsupervised Training of PLDA with Variational Bayes.pdf:pdf},
isbn = {978-3-319-13622-6},
issn = {0302-9743},
keywords = {plda,speaker recognition,unsupervised training},
month = {nov},
pages = {69--78},
publisher = {Springer International Publishing},
series = {Lecture Notes in Artificial Intelligence},
title = {{Unsupervised Training of PLDA with Variational Bayes}},
url = {http://link.springer.com/chapter/10.1007/978-3-319-13623-3{\_}8},
year = {2014}
}
@misc{villalba-patentrel,
author = {Villalba, Jes{\'{u}}s and Vaquero, Carlos and Buera, Luis},
title = {{Estimation of reliability in speaker recognition}},
year = {2014}
}
@inproceedings{villalba-is13-plda2cht,
address = {Lyon, France},
author = {Villalba, Jes{\'{u}}s and Diez, Mireia and Varona, Amparo and Lleida, Eduardo},
booktitle = {Proceedings of the 14th Annual Conference of the International Speech Communication Association, Interspeech 2013},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba et al. - 2013 - Handling Recordings Acquired Simultaneously over Multiple Channels with PLDA.pdf:pdf},
issn = {2308-457X},
month = {aug},
pages = {2509 -- 2513},
publisher = {ISCA},
title = {{Handling Recordings Acquired Simultaneously over Multiple Channels with PLDA}},
url = {http://www.mendeley.com/download/public/1833661/5999411364/05543660b49e8719b7be6ccc2cb8f1ecdc3b42ae/dl.pdf},
year = {2013}
}
@inproceedings{villalba-icassp13,
abstract = {In this work, we address the problem of having i-vectors that have been produced in different channel conditions. Traditionally, this problem has been handled training the LDA covariance matrices pooling the data of all the conditions or averaging the covariance matrices of each condition in different ways. We present a PLDA variant that we call, multichannel SPLDA, where the speaker space distribution is common to all i-vectors and the channel space distribution depends on the type of channel where the segment has been recorded. We test our approach on the telephone part of the NIST SRE10 extended condition where we have added some additive noises to the test segments. We compare results of a SPLDA model trained only with clean data, SPLDA trained with pooled noisy and clean data and our MCSPLDA model.},
address = {Vancouver, British Columbia, Canada},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013},
doi = {10.1109/ICASSP.2013.6638971},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Lleida - 2013 - Handling i-Vectors from Different Recording Conditions Using Multi-Channel Simplified PLDA in Speaker Recognit.pdf:pdf},
issn = {1520-6149},
month = {may},
pages = {6763 -- 6767},
publisher = {IEEE},
title = {{Handling i-Vectors from Different Recording Conditions Using Multi-Channel Simplified PLDA in Speaker Recognition}},
url = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=6638971},
year = {2013}
}
@inproceedings{villalba-is13-bnrel,
address = {Lyon, France},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo and Ortega, Alfonso and Miguel, Antonio},
booktitle = {Proceedings of the 14th Annual Conference of the International Speech Communication Association, Interspeech 2013},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba et al. - 2013 - A New Bayesian Network to Assess the Reliability of Speaker Verification Decisions.pdf:pdf},
issn = {2308-457X},
month = {aug},
pages = {3132 -- 3136},
publisher = {ISCA},
title = {{A New Bayesian Network to Assess the Reliability of Speaker Verification Decisions}},
url = {http://www.mendeley.com/download/public/1833661/5999411344/bba5611d72639a455f0abba80f605d11b6aaedb9/dl.pdf},
year = {2013}
}
@inproceedings{villalba-is13-i3a,
address = {Lyon, France},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo and Ortega, Alfonso and Miguel, Antonio},
booktitle = {Proceedings of the 14th Annual Conference of the International Speech Communication Association, Interspeech 2013},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba et al. - 2013 - The I3A Speaker Recognition System for NIST SRE12 Post-evaluation Analysis.pdf:pdf},
issn = {2308-457X},
month = {aug},
pages = {3679 -- 3683},
publisher = {ISCA},
title = {{The I3A Speaker Recognition System for NIST SRE12: Post-evaluation Analysis}},
url = {http://www.mendeley.com/download/public/1833661/5999411354/ce9884d7bb7d3cb1a97bc3023aab206491439b08/dl.pdf},
year = {2013}
}
@inproceedings{dcastan-icassp13-fa,
address = {Vancouver, British Columbia, Canada},
author = {Cast{\'{a}}n, Diego and Ortega, Alfonso and Villalba, Jes{\'{u}}s and Miguel, Antonio and Lleida, Eduardo},
booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013},
doi = {10.1109/ICASSP.2013.6637755},
file = {:Users/villalba/Documents/Mendeley Desktop//Cast{\'{a}}n et al. - 2013 - Segmentation-by-Classification System Based on Factor Analysis.pdf:pdf},
issn = {1520-6149},
month = {may},
pages = {783 -- 787},
publisher = {IEEE},
title = {{Segmentation-by-Classification System Based on Factor Analysis}},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6637755},
year = {2013}
}
@inproceedings{rodriguezfuentes-blz,
abstract = {This paper describes the most relevant features of a collaborative multi-site submission to the NIST 2011 Language Recognition Evaluation (LRE), consisting of one primary and three contrastive systems, each fusing different combinations of 13 state-of-the-art (acoustic and phonotactic) language recognition subsystems. The collaboration focused on collecting and sharing training data for those target languages for which few development data were provided by NIST, and on defining a common development dataset to train backend and fusion parameters and select the best fusions. Official and post-key results are presented and compared, revealing that the greedy approach applied to select the best fusions provided suboptimal but very competitive performance. Several factors contributed to the high performance attained by BLZ systems, including the availability of training data for low resource target languages, the reliability of the development dataset (consisting only of data audited by NIST), the diversity of modeling approaches, features and datasets in the systems considered for fusion, and the effectiveness of the search for optimal fusions.},
address = {Portland, Oregon, USA},
author = {Rodr{\'{i}}guez-Fuentes, Luis Javier and Penagarikano, Mikel and Varona, Amparo and Diez, Mireia and Abad, Alberto and Villalba, Jes{\'{u}}s and Ortega, Alfonso and Lleida, Eduardo},
booktitle = {Proceedings of the 13th Annual Conference of the International Speech Communication Association, Interspeech 2012},
file = {:Users/villalba/Documents/Mendeley Desktop//Rodr{\'{i}}guez-Fuentes et al. - 2012 - The BLZ Submission to the NIST 2011 LRE Data Collection, System Development and Performance.pdf:pdf},
month = {sep},
publisher = {ISCA},
title = {{The BLZ Submission to the NIST 2011 LRE: Data Collection, System Development and Performance}},
year = {2012}
}
@inproceedings{villalba-sre12,
address = {Orlando, Florida, USA},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo and Ortega, Alfonso and Miguel, Antonio},
booktitle = {NIST SRE12 Speaker Recognition Workshop},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba et al. - 2012 - I3A SRE12 System Description.pdf:pdf},
month = {dec},
title = {{I3A SRE12 System Description}},
url = {http://www.mendeley.com/download/public/1833661/5363803174/ac7ad01c801c9fed90da012a9a03353fe159c43d/dl.pdf},
year = {2012}
}
@inproceedings{villalba-jrbp12,
address = {Las Palmas de Gran Canaria, Spain},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of the VI Jornadas de Reconocimiento Biometrico de Personas, JRBP 2012},
editor = {Alonso, Jes{\'{u}}s and Travieso, Carlos},
file = {:Users/villalba/Documents/Mendeley Desktop//Villalba, Lleida - 2012 - Bayesian Two-Covariance Model for Speaker Recognition A Comparative between Integrating Out the Speakers Mean,.pdf:pdf},
issn = {978-84-695-0695-0},
month = {jan},
pages = {179--188},
title = {{Bayesian Two-Covariance Model for Speaker Recognition: A Comparative between Integrating Out the Speakers Mean, Between-Speaker and Within-Speaker Covariances}},
url = {http://www.mendeley.com/download/public/1833661/4531600845/bc6cf61e087f161a91c334e537655d8b04764536/dl.pdf},
year = {2012}
}
@inproceedings{villalba-plda-adapt,
address = {Singapore},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of Odyssey 2012 - The Speaker and Language Recognition Workshop},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Lleida - 2012 - Bayesian Adaptation of PLDA Based Speaker Recognition to Domains with Scarce Development Data.pdf:pdf},
month = {jun},
publisher = {COLIPS},
title = {{Bayesian Adaptation of PLDA Based Speaker Recognition to Domains with Scarce Development Data}},
url = {http://www.mendeley.com/download/public/1833661/4877485842/34732616706df85da62e10512ff991679baf1ddd/dl.pdf},
year = {2012}
}
@inproceedings{villalba-bay2cov-is2011,
abstract = {We propose a variational Bayes solution to integrate out the model parameters in a generative i-vector speaker recognizer. The existing state-of-the-art in g$\backslash$ enerative i-vector modelling plugs in fixed maximum-likelihood point-estimates of model parameters. This recipe may suffer from over-fitting of especially th$\backslash$ e between-speaker covariance. We show how to integrate out the between-speaker covariance and demonstrate dramatic improvements on NIST SRE 2010.},
address = {Florence, Italy},
author = {Villalba, Jes{\'{u}}s and Brummer, Niko},
booktitle = {Proceedings of the 12th Annual Conference of the International Speech Communication Association, Interspeech 2011},
file = {:Users/villalba/Documents/Mendeley Desktop//Villalba, Brummer - 2011 - Towards Fully Bayesian Speaker Recognition Integrating Out the Between-Speaker Covariance.pdf:pdf},
issn = {1990-9772},
keywords = {i-vectors,speaker recognition,variational Bayes},
month = {aug},
pages = {505--508},
publisher = {ISCA},
title = {{Towards Fully Bayesian Speaker Recognition: Integrating Out the Between-Speaker Covariance}},
url = {http://www.mendeley.com/download/public/1833661/4309852002/79830fac3c05c6e2c18ea86b38c89792e4369533/dl.pdf},
year = {2011}
}
@inproceedings{villalba-replay,
abstract = {In this paper, we describe a system for detecting spoofing attacks on speaker verification systems. We understand as spoofing the fact of impersonating a legitimate user. We focus on detecting two types of low technology spoofs. On the one side, we try to expose if the test segment is a far-field microphone recording of the victim that has been replayed on a telephone handset using a loudspeaker. On the other side, we want to determine if the recording has been created by cutting and pasting short recordings to forge the sentence requested by a text dependent system. This kind of attacks is of critical importance for security applications like access to bank accounts. To detect the first type of spoof we extract several acoustic features from the speech signal. Spoofs and non-spoof segments are classified using a support vector machine (SVM). The cut and paste is detected comparing the pitch and MFCC contours of the enrollment and test segments using dynamic time warping (DTW). We performed experiments using two databases created for this purpose. They include signals from land line and GSM telephone channels of 20 different speakers. We present results of the performance separately for each spoofing detection system and the fusion of both. We have achieved error rates under 10$\backslash${\%} for all the conditions evaluated. We show the degradation on the speaker verification performance in the presence of this kind of attack and how to use the spoofing detection to mitigate that degradation.},
address = {Mataro, Spain},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of the IEEE International Carnahan Conference on Security Technology, ICCST 2011},
doi = {10.1109/CCST.2011.6095943},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Lleida - 2011 - Preventing Replay Attacks on Speaker Verification Systems.pdf:pdf},
isbn = {978-1-4577-0902-9},
issn = {1071-6572},
keywords = {and paste,cut,far-field,forgery,replay attack,speaker verification,spoofing},
month = {sep},
pages = {284--291},
publisher = {IEEE},
title = {{Preventing Replay Attacks on Speaker Verification Systems}},
url = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=6095943{\&}tag=1},
year = {2011}
}
@inproceedings{Rodriguez-Fuentes2011,
abstract = {Best language recognition performance is commonly obtained by fusing the scores of several heterogeneous systems. Regardless the fusion approach, it is assumed that different systems may contribute complementary information, either because they are developed on different datasets, or because they use different features or different modeling approaches. Most authors apply fusion as a final resource for improving performance based on an existing set of systems. Though relative performance gains decrease as larger sets of systems are considered, best performance is usually attained by fusing all the available systems, which may lead to high computational costs. In this paper, we aim to discover which technologies combine the best through fusion and to analyse the factors (data, features, modeling methodologies, etc.) that may explain such a good performance. Results are presented and discussed for a number of systems provided by the participating sites and the organizing team of the Albayzin 2010 Language Recognition Evaluation. We hope the conclusions of this work help research groups make better decisions in developing language recognition technology.},
address = {Big Island, Hawaii, USA},
author = {Rodr{\'{i}}guez-Fuentes, Luis Javier and Penagarikano, Mikel and Varona, Amparo and Diez, Mireia and Bordel, German and Mart{\'{i}}nez, David and Villalba, Jes{\'{u}}s and Miguel, Antonio and Ortega, Alfonso and Lleida, Eduardo and Abad, Alberto and Koller, Oscar and Trancoso, Isabel and Lopez-Otero, Paula and Docio-Fernandez, Laura and Garcia-Mateo, Carmen and Saeidi, Rahim and Soufifar, Mehdi and Kinnunen, Tomi and Svendsen, Torbjorn and Franti, Pasi},
booktitle = {Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2011},
doi = {10.1109/ASRU.2011.6163961},
file = {:Users/villalba/Documents/Mendeley Desktop//Rodr{\'{i}}guez-fuentes et al. - 2011 - Multi-site Heterogeneous System Fusions for the Albayzin 2010 Language Recognition Evaluation.pdf:pdf},
isbn = {9781467303668},
month = {dec},
organization = {GTTS, Department of Electricity and Electronics, University of the Basque Country, Spain},
pages = {377--382},
publisher = {IEEE},
title = {{Multi-site heterogeneous system fusions for the Albayzin 2010 Language Recognition Evaluation}},
year = {2011}
}
@inproceedings{villalba-sre11,
address = {Atlanta, Georgia, USA},
author = {Villalba, Jes{\'{u}}s and Brummer, Niko and Lleida, Eduardo},
booktitle = {NIST SRE11 Speaker Recognition Workshop},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Brummer, Lleida - 2011 - Fully Bayesian Likelihood Ratios vs i-vector Length Normalization in Speaker Recognition Systems.pdf:pdf},
month = {dec},
title = {{Fully Bayesian Likelihood Ratios vs i-vector Length Normalization in Speaker Recognition Systems}},
url = {http://www.mendeley.com/download/public/1833661/4531600835/f068396135c29928626c597a5bbbe2c0fd0dd913/dl.pdf},
year = {2011}
}
@inproceedings{martinez-albayzin10,
abstract = {This paper describes the two systems submitted to the Albayzin 2010 Language Recognition Evaluation by I3A. This evaluation is similar to the one organized by NIST every 2 years, but the languages to be recognized are those spoken in the Iberian peninsula (Spanish, Catalan, Basque, Galician and Portuguese) plus English. Both submissions are a fusion of five phonotactic and three acoustic subsystems. The only difference between them is the normalization and fusion of the scores. State-of-the art methods for Language Recognition are adapted to and investigated in the KALAKA-2 database. Our primary system was ranked in the first position of the evaluation.},
address = {Florence, Italy},
author = {Mart{\'{i}}nez, David and Villalba, Jes{\'{u}}s and Miguel, Antonio and Ortega, Alfonso and Lleida, Eduardo},
booktitle = {Proceedings of the 12th Annual Conference of the International Speech Communication Association, Interspeech 2011},
file = {:Users/villalba/Documents/Mendeley Desktop/Mart{\'{i}}nez et al. - 2010 - VIVOLAB-UZ Language Recognition System for Albayzin 2010 LRE(2).pdf:pdf},
issn = {1990-9772},
month = {aug},
pages = {849--852},
publisher = {ISCA},
title = {{I3A Language Recognition System for Albayzin 2010 LRE}},
url = {http://www.mendeley.com/download/public/1833661/3949249582/97bf7f1a1dc9f09ee615dc5c9a1d734d1e3c6dff/dl.pdf http://www.mendeley.com/download/public/1833661/4309851992/8aa86f62ef0eae4f95bb4b8e490b52f6c5373f87/dl.pdf},
year = {2011}
}
@article{cvaquero-svsummed,
author = {Vaquero, Carlos and Villalba, Jes{\'{u}}s and Ortega, Alfonso and Lleida, Eduardo},
editor = {Ruiz, Jos{\'{e}} and Nolazco-Flores, Juan A.},
file = {:Users/villalba/Documents/Mendeley Desktop/Vaquero et al. - 2011 - Speaker Verification on Summed Channel Conditions with Confidence Measures.pdf:pdf;:Users/villalba/Documents/Mendeley Desktop/Vaquero et al. - 2011 - Speaker Verification on Summed Channel Conditions with Confidence Measures.doc:doc},
issn = {1405-5546},
journal = {Computacion y Sistemas},
number = {1},
pages = {27--37},
series = {Reconocimiento de Patrones Miner{\'{i}}a de Datos y Aplicaciones},
title = {{Speaker Verification on Summed Channel Conditions with Confidence Measures}},
url = {http://cys.cic.ipn.mx/ojs/index.php/CyS/article/viewFile/1291/1383},
volume = {15},
year = {2011}
}
@inproceedings{castan-hmmfa,
abstract = {This paper investigates the performance of a Factor Analysis stage in audio segmentation systems. The system described here is designed to segment and classify the audio files coming from broadcast programs into five different classes: speech, speech with noise, speech with music, music or others. This task was recently proposed as a competitive evaluation organized by the Spanish Network on Speech Technologies as part of the conference FALA 2010. The system proposed here makes use of a hierarchical structure in two steps with two different acoustic features. First, the system decides among music, speech with music or the rest of the classes by using HMM/GMM and a smoothed combination of MFCC and Chroma as feature vectors. Next, the system classifies speech and speech with noise by using FA and MFCC as acoustic features. The results shows that, with this configuration, the error rate achieved is lower than the one obtained by the best system presented in the FALA 2010 evaluation.},
address = {Florence, Italy},
author = {Cast{\'{a}}n, Diego and Vaquero, Carlos and Ortega, Alfonso and Mart{\'{i}}nez, David and Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of the 12th Annual Conference of the International Speech Communication Association, Interspeech 2011},
file = {:Users/villalba/Documents/Mendeley Desktop/Cast{\'{a}}n et al. - 2011 - Hierarchical Audio Segmentation with HMM and Factor Analysis in Broadcast News Domain.pdf:pdf},
issn = {1990-9772},
month = {aug},
pages = {421--424},
publisher = {ISCA},
title = {{Hierarchical Audio Segmentation with HMM and Factor Analysis in Broadcast News Domain}},
url = {http://www.mendeley.com/download/public/1833661/4309851982/4aafe7b7c68b14173507b6e9d67663ab4b704dad/dl.pdf},
year = {2011}
}
@inproceedings{villalba-farfield,
abstract = {In this paper, we describe a system for detecting spoofing attacks on speaker verification systems. By spoofing we mean an attempt to impersonate a legitimate user. We focus on detecting if the test segment is a far-field microphone recording of the victim. This kind of attack is of critical importance in security applications like access to bank accounts. We present experiments on databases created for this purpose, including land line and GSM telephone channels. We present spoofing detection results with EER between 0{\%} and 9{\%} depending on the condition. We show the degradation on the speaker verification performance in the presence of this kind of attack and how to use the spoofing detection to mitigate that degradation.},
address = {Brandenburg, Germany},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Biometrics and ID Management, Proceedings of the COST 2101 European Workshop, BioID 2011},
doi = {10.1007/978-3-642-19530-3_25},
editor = {Vielhauer, Claus and Dittmann, Jana and Drygajlo, Andrzej and Juul, Niels and Fairhust, Michael},
file = {:Users/villalba/Documents/Mendeley Desktop//Villalba, Lleida - 2011 - Detecting Replay Attacks from Far-Field Recordings on Speaker Verification Systems.pdf:pdf},
isbn = {978-3-642-19530-3},
issn = {0302-9743},
keywords = {far-field,replay attack,speaker verification,spoofing},
month = {mar},
pages = {274--285},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
title = {{Detecting Replay Attacks from Far-Field Recordings on Speaker Verification Systems}},
url = {http://link.springer.com/chapter/10.1007/978-3-642-19530-3{\_}25},
year = {2011}
}
@inproceedings{Vaquero2010,
address = {Makuhari, Chiba, Japan},
author = {Vaquero, Carlos and Ortega, Alfonso and Villalba, Jes{\'{u}}s and Miguel, Antonio and Lleida, Eduardo},
booktitle = {Proceedings of the 11th Annual Conference of the International Speech Communication Association, Interspeech 2010},
file = {:Users/villalba/Documents/Mendeley Desktop//Vaquero et al. - 2010 - Confidence Measures for Speaker Segmentation and their Influence on Speaker Verification.pdf:pdf},
issn = {1990-9772},
month = {sep},
pages = {2310--2313},
publisher = {ISCA},
title = {{Confidence Measures for Speaker Segmentation and their Influence on Speaker Verification}},
url = {http://www.mendeley.com/download/public/1833661/3949229592/e9a4ff4c9952defc1fb37b81523341c380348d14/dl.pdf},
year = {2010}
}
@inproceedings{Vaquero2010a,
address = {Huesca, Spain},
author = {Vaquero, Carlos and Ortega, Alfonso and Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of the V Jornadas de Reconocimiento Biometrico de Personas, JRBP 2010},
file = {:Users/villalba/Documents/Mendeley Desktop//Vaquero et al. - 2010 - Confidence Measures and Hypothesis Selection Strategies for Speaker Segmentation.pdf:pdf},
keywords = {vaquero-jrbp},
month = {sep},
pages = {67--74},
title = {{Confidence Measures and Hypothesis Selection Strategies for Speaker Segmentation}},
url = {http://www.mendeley.com/download/public/1833661/3949230292/1d5b0a5a9a0e4d790916b17d993b6b92168d4f0e/dl.pdf},
year = {2010}
}
@inproceedings{villalba-sre10,
address = {Huesca, Spain},
author = {Villalba, Jes{\'{u}}s and Vaquero, Carlos and Lleida, Eduardo and Ortega, Alfonso and Miguel, Antonio},
booktitle = {Proceedings of the V Jornadas de Reconocimiento Biometrico de Personas, JRBP 2010},
file = {:Users/villalba/Documents/Mendeley Desktop//Villalba et al. - 2010 - I3A NIST SRE2010 System Description.pdf:pdf},
month = {sep},
pages = {241--250},
title = {{I3A NIST SRE2010 System Description}},
url = {http://www.mendeley.com/download/public/1833661/3949230302/8772cb1e3df09db42090e2318c333e2e33cfe7be/dl.pdf},
year = {2010}
}
@inproceedings{villalba-spkvperformance,
address = {Vigo, Spain},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo},
booktitle = {Proceedings of Fala 2010},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba, Lleida - 2010 - Speaker Verification Performance Degradation against Spoofing and Tampering Attacks.pdf:pdf},
isbn = {978-84-8158-510-0},
month = {nov},
pages = {131--134},
title = {{Speaker Verification Performance Degradation against Spoofing and Tampering Attacks}},
url = {http://www.mendeley.com/download/public/1833661/3949230272/ac77ebb3331eedd65dd6affc5a12c9d353c776f3/dl.pdf},
year = {2010}
}
@inproceedings{dayana-missingfeature,
address = {Vigo, Spain},
author = {Ribas, Dayana and Villalba, Jes{\'{u}}s and Lleida, Eduardo and Calvo, Jos{\'{e}} R.},
booktitle = {Proceedings of Fala 2010},
isbn = {978-84-8158-510-0},
month = {nov},
pages = {115--118},
title = {{Missing Feature Techniques Combination for Speaker Recognition in Noisy Environment}},
year = {2010}
}
@misc{villalba-patentcp,
author = {Villalba, Jes{\'{u}}s and Ortega, Alfonso and Lleida, Eduardo and Vandela, Sara and Garc{\'{i}}a-Gomar, Marta},
title = {{Cut and paste spoofing detection using dynamic time warping}},
year = {2009}
}
@inproceedings{Villalba2009,
address = {Reggio Emilia, Italy},
author = {Villalba, Jes{\'{u}}s and Lleida, Eduardo and Ortega, Alfonso and Vaquero, Carlos and Miguel, Antonio},
booktitle = {Proceedings of the 11th Conference of the Italian Association for Artificial Intelligence},
file = {:Users/villalba/Documents/Mendeley Desktop/Villalba et al. - 2009 - I3A System for Evalita 2009 Speaker Verification Application Evaluation.pdf:pdf},
month = {dec},
title = {{I3A System for Evalita 2009 Speaker Verification Application Evaluation}},
url = {http://www.evalita.it/sites/evalita.fbk.eu/files/proceedings2009/Speaker Identity Verification/Application/SIV{\_}APPLICATION{\_}UNI{\_}ZARAGOZA.pdf},
year = {2009}
}
@inproceedings{Villalba2008,
address = {Valladolid, Spain},
author = {Villalba, Jes{\'{u}}s and Vaquero, Carlos and Lleida, Eduardo and Ortega, Alfonso and Miguel, Antonio and Garcia, Jose E. and Buera, Luis and Saz, {\'{O}}scar},
booktitle = {Proceedings of the IV Jornadas de Reconocimiento Biometrico de Personas, JRBP 2008},
file = {:Users/villalba/Documents/Mendeley Desktop//Villalba et al. - 2008 - Experiencia del I3A en la Evaluaci{\'{o}}n de Reconocimiento de Locutor NIST 2008.pdf:pdf},
month = {sep},
title = {{Experiencia del I3A en la Evaluaci{\'{o}}n de Reconocimiento de Locutor NIST 2008}},
url = {http://www.mendeley.com/download/public/1833661/3948390932/fdd3f2ee82702e40498fa82175e0e764915752ad/dl.pdf},
year = {2008}
}
@inproceedings{Buera2006,
address = {Sevilla, Spain},
author = {Buera, Luis and Lleida, Eduardo and Rosas, Juan Diego and Villalba, Jes{\'{u}}s and Miguel, Antonio and Ortega, Alfonso and Saz, {\'{O}}scar},
booktitle = {Proceedings of the III Jornadas de Reconocimiento Biom{\'{e}}trico de Personas, JRBP 2006},
file = {:Users/villalba/Documents/Mendeley Desktop//Buera et al. - 2006 - Verificaci{\'{o}}n e Identificaci{\'{o}}n de Locutor con Normalizaci{\'{o}}n de Vectores de Caracter{\'{i}}sticas en Entornos Ac{\'{u}}stic.pdf:pdf},
month = {nov},
title = {{Verificaci{\'{o}}n e Identificaci{\'{o}}n de Locutor con Normalizaci{\'{o}}n de Vectores de Caracter{\'{i}}sticas en Entornos Ac{\'{u}}sticos Adversos}},
url = {http://www.mendeley.com/download/public/1833661/3948388942/a7c9b3ee70bb13a4302e72474350ab4d881b20eb/dl.pdf},
year = {2006}
}
@inproceedings{Buera2005,
abstract = {In adverse acoustic conditions, speaker verification and identification system rates degrade very significatively. In order to compensate this effect, several techniques can be applied. In this paper Phoneme Dependent Multi-Environment Models based LInear Normalization, PD-MEMLIN, is presented as a solution in order to clean signal in a early processing step. In this algorithm, clean and noisy spaces are modelled by mixtures of gaussians for each phoneme, and a linear transformation is learnt with stereo data for each phoneme pair of gaussians: one for the clean space and the other one for the noisy space. Some experiments with Spanish SpeechDat Car database were carried out in order to study the behavior of the proposed technique in verification and identification tasks. With an UBM-GMM verification system, important average improvement in Equal- Error Rate (EER) is obtained (70.20{\%}). The improvement in identification task with aGMMsystem is 48.69{\%}.},
address = {Alghero, Italy},
author = {Buera, Luis and Lleida, Eduardo and Rosas, Juan Diego and Villalba, Jes{\'{u}}s and Miguel, Antonio and Ortega, Alfonso and Saz, {\'{O}}scar},
booktitle = {Summer School for Advanced studies on Biometrics for Secure Authentication Multimodality ans System Integration},
file = {:Users/villalba/Documents/Mendeley Desktop//Buera et al. - 2005 - Speaker verification and identification using Phoneme Dependent Multi-Environment Models based LInear Normalizatio.pdf:pdf},
month = {jun},
title = {{Speaker verification and identification using Phoneme Dependent Multi-Environment Models based LInear Normalization in adverse and dynamic acoustic environments}},
url = {http://www.mendeley.com/download/public/1833661/3949171112/3c7d9d917301713f0b6de0d1742dedcf91efb45e/dl.pdf},
year = {2005}
}

repository: jesus-villalba/academic-kickstart

repo_name: jesus-villalba/academic-kickstart


text:
//go:build !wasm
// +build !wasm

package shell

import (
	"context"
	"fmt"
	"regexp"
	"sort"
	"strings"

	"github.com/anz-bank/pkg/log"
	"github.com/arr-ai/wbnf/parser"
	"github.com/go-errors/errors"

	"github.com/arr-ai/arrai/syntax"
)

var cmdRe = regexp.MustCompile(`^/[a-zA-Z_]\w*[ \t]*`)

func isCommand(line string) bool {
	return cmdRe.MatchString(line)
}

func tryRunCommand(ctx context.Context, line string, shellData *shellInstance) error {
	var name string
	if name = cmdRe.FindString(line); name == "" {
		return errors.Errorf("%s is not a command", line)
	}
	name = strings.TrimSpace(name[1:])
	line = strings.TrimSpace(cmdRe.ReplaceAllString(line, ""))
	cmd, isCmd := shellData.cmds[name]
	if !isCmd {
		return errors.Errorf("command %s not found", name)
	}
	return cmd.process(ctx, line, shellData)
}

type shellCmd interface {
	names() []string
	process(ctx context.Context, line string, shellData *shellInstance) error
}

type setCmd struct{}

func (sc *setCmd) names() []string {
	return []string{"set"}
}

func (sc *setCmd) process(ctx context.Context, line string, shellData *shellInstance) error {
	identRe := regexp.MustCompile(`^(?P<ident>\.|[$@A-Za-z_][0-9$@A-Za-z_]*)[ \t]+=`)
	identMatches := identRe.FindStringSubmatch(line)
	if len(identMatches) != 2 {
		return errors.Errorf(`/set command error, usage: /set <name> = <expr>`)
	}
	name := identMatches[1]
	expr := identRe.ReplaceAllString(line, "")
	val, err := shellEval(ctx, expr, shellData.scope)
	if err != nil {
		return err
	}
	shellData.scope = shellData.scope.With(name, val)
	return nil
}

type unsetCmd struct{}

func (uc *unsetCmd) names() []string {
	return []string{"unset"}
}

func (uc *unsetCmd) process(ctx context.Context, line string, shellData *shellInstance) error {
	ident := regexp.MustCompile(`^(\.|[$@A-Za-z_][0-9$@A-Za-z_]*)`).FindString(line)
	if ident == "" {
		return errors.Errorf(`/unset command error, usage: /unset <name>`)
	}
	shellData.scope = shellData.scope.Without(ident)
	return nil
}

type exitError struct{}

func (exitError) Error() string {
	return "exiting interactive shell"
}

type exitCommand struct{}

func (*exitCommand) names() []string {
	return []string{"exit"}
}

func (ec *exitCommand) process(ctx context.Context, _ string, _ *shellInstance) error {
	return exitError{}
}

type upFrameCmd struct{}

func (*upFrameCmd) names() []string {
	return []string{"up", "u"}
}

func (*upFrameCmd) process(ctx context.Context, _ string, sh *shellInstance) error {
	return changeFrame(ctx, sh.currentFrameIndex-1, sh)
}

type downFrameCmd struct{}

func (d *downFrameCmd) names() []string {
	return []string{"down", "d"}
}

func (*downFrameCmd) process(ctx context.Context, _ string, sh *shellInstance) error {
	return changeFrame(ctx, sh.currentFrameIndex+1, sh)
}

func changeFrame(ctx context.Context, i int, sh *shellInstance) error {
	if i < 0 || i >= len(sh.frames) {
		return fmt.Errorf("frame index out of range, frame length: %d", len(sh.frames))
	}
	sh.currentFrameIndex = i
	log.Infof(ctx, "Stack: %d\n%s\n", i, sh.frames[i].GetSource().Context(parser.DefaultLimit))
	sh.scope = syntax.StdScope().Update(sh.frames[i].GetScope())
	return nil
}

func initCommands() (map[string]shellCmd, []string) {
	cmds := []shellCmd{&setCmd{}, &unsetCmd{}, &exitCommand{}, &upFrameCmd{}, &downFrameCmd{}}
	cmdMap := make(map[string]shellCmd)
	var preds []string
	for _, cmd := range cmds {
		for _, n := range cmd.names() {
			cmdMap[n] = cmd
			preds = append(preds, fmt.Sprintf("/%s ", n))
		}
	}
	sort.Strings(preds)
	return cmdMap, preds
}

repository: arr-ai/arrai

license_type: permissive

repo_name: arr-ai/arrai

branch_name: refs/heads/master

gha_language: Go

extension: go


text:
@InProceedings{mladenov14,
  title = {{Efficient Lifting of MAP LP Relaxations Using k-Locality}},
  author = {Mladenov, Martin and Kersting, Kristian and Globerson, Amir},
  pages = {623-632},
  abstract = {Inference in large scale graphical models is an important task in many domains, and in particular for probabilistic relational models (e.g,. Markov logic networks). Such models often exhibit considerable symmetry, and it is a challenge to devise algorithms that exploit this symmetry to speed up inference.   Here we address this task in the context of the MAP inference problem and its linear programming relaxations. We show that symmetry in these problems  can be discovered using an elegant algorithm known as the $k$-dimensional Weisfeiler-Lehman (k-WL) algorithm. We run k-WL on the original graphical model, and not on the far larger graph of the linear program (LP) as proposed in earlier work in the field. Furthermore, the algorithm is polynomial and thus far more practical than other previous approaches which rely on orbit partitions that are GI complete to find. The fact that k-WL can be used in this manner follows from the recently introduced notion of $k$-local LPs and their relation to Sherali Adams relaxations of graph automorphisms. Finally, for relational models such as Markov logic networks, the benefits of our approach are even more dramatic, as we can discover symmetries in the original domain graph, as opposed to running lifting on the much larger grounded model.},
}

license: MIT

repository: mreid/papersite

repo_name: mreid/papersite

gha_license_id: MIT

gha_language: TeX

extension: bib


text:
/*
 * Copyright 2012-2019 the original author or authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package StarterMySqlGorm

import (
	"github.com/go-spring/spring-base/log"
	"github.com/go-spring/spring-core/database"
	"github.com/go-spring/spring-core/gs"
	"github.com/go-spring/spring-core/gs/arg"
	"github.com/go-spring/spring-core/gs/cond"
	"gorm.io/driver/mysql"
	"gorm.io/gorm"
)

type Factory struct {
	Logger *log.Logger `logger:""`
}

func (factory *Factory) CreateDB(config database.Config) (*gorm.DB, error) {
	factory.Logger.Infof("open gorm mysql %s", config.URL)
	db, err := gorm.Open(mysql.Open(config.URL))
	if err != nil {
		return nil, err
	}
	return db, nil
}

func init() {
	gs.Object(&Factory{})
	gs.Provide((*Factory).CreateDB, arg.R1("${gorm}")).
		Name("GormDB").
		On(cond.OnMissingBean(gs.BeanID((*gorm.DB)(nil), "GormDB")))
}

repository: go-spring/go-spring

repo_name: go-spring/go-spring


text:
// Code generated by go-swagger; DO NOT EDIT.

package models

// This file was generated by the swagger tool.
// Editing this file might prove futile when you re-run the swagger generate command

import (
	"context"
	"encoding/json"

	"github.com/go-openapi/errors"
	"github.com/go-openapi/strfmt"
	"github.com/go-openapi/validate"
)

// SubscriptionStatus Possible subscription status values.
//
// swagger:model SubscriptionStatus
type SubscriptionStatus string

const (

	// SubscriptionStatusPENDING captures enum value "PENDING"
	SubscriptionStatusPENDING SubscriptionStatus = "PENDING"

	// SubscriptionStatusACTIVE captures enum value "ACTIVE"
	SubscriptionStatusACTIVE SubscriptionStatus = "ACTIVE"

	// SubscriptionStatusCANCELED captures enum value "CANCELED"
	SubscriptionStatusCANCELED SubscriptionStatus = "CANCELED"
)

// for schema
var subscriptionStatusEnum []interface{}

func init() {
	var res []SubscriptionStatus
	if err := json.Unmarshal([]byte(`["PENDING","ACTIVE","CANCELED"]`), &res); err != nil {
		panic(err)
	}
	for _, v := range res {
		subscriptionStatusEnum = append(subscriptionStatusEnum, v)
	}
}

func (m SubscriptionStatus) validateSubscriptionStatusEnum(path, location string, value SubscriptionStatus) error {
	if err := validate.EnumCase(path, location, value, subscriptionStatusEnum, true); err != nil {
		return err
	}
	return nil
}

// Validate validates this subscription status
func (m SubscriptionStatus) Validate(formats strfmt.Registry) error {
	var res []error

	// value enum
	if err := m.validateSubscriptionStatusEnum("", "body", m); err != nil {
		return err
	}

	if len(res) > 0 {
		return errors.CompositeValidationError(res...)
	}
	return nil
}

// ContextValidate validates this subscription status based on context it is used
func (m SubscriptionStatus) ContextValidate(ctx context.Context, formats strfmt.Registry) error {
	return nil
}

repository: jefflinse/square-connect

repo_name: jefflinse/square-connect

gha_language: Makefile


text:
@article{salter2011closed,
 author = {Salter, Anastasia},
 journal = {Supernatural Youth: The Rise of the Teen Hero in Literature and Popular Culture},
 pages = {157},
 publisher = {Lexington Books},
 title = {Closed Minds},
 year = {2011}
}

repository: AMSUCF/academic-kickstart

repo_name: AMSUCF/academic-kickstart


text:
package pgsql

import (
	"net/http"
	"strings"

	"github.com/go-pg/pg"

	"github.com/go-pg/pg/orm"
	"github.com/labstack/echo"
	"github.com/nguyencatpham/go-effective-study/pkg/utl/model"
)

// NewUser returns a new user database instance
func NewUser() *User {
	return &User{}
}

// User represents the client for user table
type User struct{}

// Custom errors
var (
	ErrAlreadyExists = echo.NewHTTPError(http.StatusInternalServerError, "Username or email already exists.")
)

// Create creates a new user on database
func (u *User) Create(db orm.DB, usr model.User) (*model.User, error) {
	var user = new(model.User)
	err := db.Model(user).Where("lower(username) = ? or lower(email) = ? and deleted_at is null",
		strings.ToLower(usr.Username), strings.ToLower(usr.Email)).Select()

	if err != nil && err != pg.ErrNoRows {
		return nil, ErrAlreadyExists

	}

	if err := db.Insert(&usr); err != nil {
		return nil, err
	}
	return &usr, nil
}

// View returns single user by ID
func (u *User) View(db orm.DB, id int) (*model.User, error) {
	var user = new(model.User)
	sql := `SELECT "user".*, "role"."id" AS "role__id", "role"."access_level" AS "role__access_level", "role"."name" AS "role__name"
	FROM "users" AS "user" LEFT JOIN "roles" AS "role" ON "role"."id" = "user"."role_id"
	WHERE ("user"."id" = ? and deleted_at is null)`
	_, err := db.QueryOne(user, sql, id)
	if err != nil {
		return nil, err
	}

	return user, nil
}

// Update updates user's contact info
func (u *User) Update(db orm.DB, user *model.User) error {
	return db.Update(user)
}

// List returns list of all users retrievable for the current user, depending on role
func (u *User) List(db orm.DB, qp *model.ListQuery, p *model.Pagination) ([]model.User, error) {
	var users []model.User
	q := db.Model(&users).Column("user.*", "Role").Limit(p.Limit).Offset(p.Offset).Where("deleted_at is null").Order("user.id desc")
	if qp != nil {
		q.Where(qp.Query, qp.ID)
	}
	if err := q.Select(); err != nil {
		return nil, err
	}
	return users, nil
}

// Delete sets deleted_at for a user
func (u *User) Delete(db orm.DB, user *model.User) error {
	return db.Delete(user)
}

repository: nguyencatpham/go-effective-study

repo_name: nguyencatpham/go-effective-study


text:
@article{Lynch2003105,
    title = "Hybrid {I/O} automata ",
    journal = "Information and Computation",
    volume = "185",
    number = "1",
    pages = "105 - 157",
    year = "2003",
    note = "",
    issn = "0890-5401",
    doi = "http://dx.doi.org/10.1016/S0890-5401(03)00067-1",
    url = "http://www.sciencedirect.com/science/article/pii/S0890540103000671",
    author = "Nancy Lynch and Roberto Segala and Frits Vaandrager"
}


text:
# base recipe: meta-openembedde/meta-oe/recipes-extended/rsyslog/libfastjson_0.99.8.bb
# base branch: warrior
# base commit: a74abf155d7bd6c873fd72b76369c09e5c68031c

SUMMARY = "A fork of json-c library"
HOMEPAGE = "https://github.com/rsyslog/libfastjson"

LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://COPYING;md5=a958bb07122368f3e1d9b2efe07d231f"

inherit debian-package
require recipes-debian/sources/libfastjson.inc

DEPENDS = ""

SRC_URI += " file://0001-fix-jump-misses-init-gcc-8-warning.patch"

inherit autotools

repository: miraclelinux/meta-debian-extended

repo_name: miraclelinux/meta-debian-extended

branch_name: refs/heads/warrior

gha_language: BitBake

extension: bb


text:
SECTION = "console/network"
DESCRIPTION = "rlpr makes it possible to print files on remote sites to your networked printers"
HOMEPAGE = "http://truffula.com/rlpr/"
LICENSE = "GPL"
SRC_URI = "ftp://www.truffula.com/pub/rlpr-2.05.tar.gz"

inherit autotools

do_configure() {
	oe_runconf
}

do_install() {
	make install DESTDIR=${D}
}

SRC_URI[md5sum] = "64ee8ccd94aabc90b9f40d0b2ad79e79"
SRC_URI[sha256sum] = "6b1261c8a23a58c8e174d8ee1ad53c138ed0b9211f7ea3f3efe22d16af14ba9a"


text:
package lgr

import (
	"encoding/json"
	"fmt"
	"io"
	"os"
	"path/filepath"
	"strings"
	"time"

	"github.com/Seinapp/sein/stable/go/desktop-helper/src/config"
	lumberjack "gopkg.in/natefinch/lumberjack.v2"
)

// we make sure JSONPrinter implements Printer
var _ Printer = (*JSONPrinter)(nil)

// NewJSONPrinter returns a printer that outputs data as JSON
func NewJSONPrinter() *JSONPrinter {
	return &JSONPrinter{}
}

// JSONPrinter is a printer that outputs data as JSON
type JSONPrinter struct {
	fileWritter io.WriteCloser
}

// UseLogFile will create a log file in the provided directory
func (p *JSONPrinter) UseLogFile(logDirectory string) {
	if p.fileWritter != nil {
		p.fileWritter.Close()
	}
	p.fileWritter = &lumberjack.Logger{
		Filename:   filepath.Join(logDirectory, config.HelperCLILogRelPath),
		MaxSize:    20,
		MaxBackups: 3,
		MaxAge:     30,
	}
}

// CloseLogFile will close a log file if there was one
func (p *JSONPrinter) CloseLogFile() error {
	if p.fileWritter != nil {
		return p.fileWritter.Close()
	}
	return nil
}

// Type returns TypeJSON
func (p *JSONPrinter) Type() Type {
	return TypeJSON
}

// PrintError prints an error as JSON on stderr
func (p *JSONPrinter) PrintError(e error) {
	p.print(os.Stderr, "error", e.Error(), struct {
		Error string    `json:"error"`
		At    time.Time `json:"at"`
	}{Error: e.Error(), At: time.Now().UTC()})
}

// PrintWarning prints a warning message as JSON on stderr
func (p *JSONPrinter) PrintWarning(msg string) {
	p.print(os.Stderr, "warning", msg, struct {
		Warning string    `json:"warning"`
		At      time.Time `json:"at"`
	}{Warning: msg, At: time.Now().UTC()})
}

// PrintInfo prints an info message as JSON on stderr
func (p *JSONPrinter) PrintInfo(msg string) {
	p.print(os.Stderr, "info", msg, struct {
		Info string    `json:"info"`
		At   time.Time `json:"at"`
	}{Info: msg, At: time.Now().UTC()})
}

// PrintSuccess prints a success message on stdout
func (p *JSONPrinter) PrintSuccess(msg string) {
	// let's make sure the string it's not already a json string
	if msg[0] == '{' || msg[0] == '[' {
		os.Stdout.WriteString(msg)
		p.fileWritter.Write([]byte(msg))
		return
	}

	p.print(os.Stdout, "success", msg, struct {
		Success string    `json:"success"`
		At      time.Time `json:"at"`
	}{Success: msg, At: time.Now().UTC()})
}

// print prints a message as JSON on stderr
func (p *JSONPrinter) print(out *os.File, tag, originalData string, object interface{}) {
	var msg string

	resp, err := json.Marshal(object)
	if err != nil {
		// if we could not encode the thing (which should never happen)
		// we can try to hardcode the string (which may result in an invalid
		// json)
		msg = fmt.Sprintf(`{"%s":"%s", "at":"%s"}`,
			tag,
			strings.Replace(originalData, `"`, `\\"`, -1),
			time.Now().UTC().String(),
		)
	} else {
		msg = string(resp)
	}

	msg += "\n"
	out.WriteString(msg)
	p.fileWritter.Write([]byte(msg))
}

repository: Seinapp/sein

repo_name: Seinapp/sein

gha_language: JavaScript


text:
# This script defines a download_dir variable, if it's not already defined.

# Cache the downloads in download_dir if it's defined. Otherwise, use the
# user's typical Downloads directory, if it already exists. Otherwise, use a
# Downloads subdir in the build tree.
#
if(NOT DEFINED download_dir)
  if(NOT "$ENV{HOME}" STREQUAL "" AND EXISTS "$ENV{HOME}/Downloads")
    set(download_dir "$ENV{HOME}/Downloads")
  elseif(NOT "$ENV{USERPROFILE}" STREQUAL "" AND EXISTS "$ENV{USERPROFILE}/Downloads")
    set(download_dir "$ENV{USERPROFILE}/Downloads")
  elseif(NOT "${CMAKE_CURRENT_BINARY_DIR}" STREQUAL "")
    set(download_dir "${CMAKE_CURRENT_BINARY_DIR}/Downloads")
  else()
    message(FATAL_ERROR "unexpectedly empty CMAKE_CURRENT_BINARY_DIR")
  endif()
  string(REPLACE "\\" "/" download_dir "${download_dir}")
endif()

file(MAKE_DIRECTORY "${download_dir}")
if(NOT EXISTS "${download_dir}")
  message(FATAL_ERROR "could not find or make Downloads directory")
endif()

repository: OpenChemistry/openchemistry

repo_name: OpenChemistry/openchemistry

gha_language: CMake

extension: cmake


text:
@InProceedings{valdez2012using,
  title = {Using mixed node publication network graphs for analyzing success in interdisciplinary teams},
  author = {Andr{\'e} {Calero Valdez} and Anne Kathrin Schaar and Martina Ziefle and Andreas Holzinger and Sabina Jeschke and Christian Brecher},
  editor = {{TBC}},
  booktitle = {International Conference on Active Media Technology},
  pages = {606--617},
  year = {2012},
  organization = {Springer, Berlin, Heidelberg},
  date = {2012-01-01},
}

repository: Sumidu/academic-kickstart

repo_name: Sumidu/academic-kickstart


text:
@article{Moon-2021-Probing,
    title = "Probing Metal-Dependent Phosphate Binding for the Catalysis of the 17E DNAzyme",
    author = "Moon, Woohyun J.  and
      Huang, Po-Jung Jimmy  and
      Liu, Juewen",
    journal = "Biochemistry, Volume 60, Issue 24",
    volume = "60",
    number = "24",
    year = "2021",
    publisher = "American Chemical Society (ACS)",
    url = "https://aclanthology.org/G21-128001",
    doi = "10.1021/acs.biochem.1c00091",
    pages = "1909--1918",
}

repository: gwf-uwaterloo/gwf-publications

repo_name: gwf-uwaterloo/gwf-publications

branch_name: refs/heads/main

gha_language: Python


text:
// Code generated by smithy-go-codegen DO NOT EDIT.

package types_test

import (
	"fmt"
	"github.com/aws/aws-sdk-go-v2/internal/protocoltest/awsrestjson/types"
)

func ExampleMyUnion_outputUsage() {
	var union types.MyUnion
	// type switches can be used to check the union value
	switch v := union.(type) {
	case *types.MyUnionMemberBlobValue:
		_ = v.Value // Value is []byte

	case *types.MyUnionMemberBooleanValue:
		_ = v.Value // Value is bool

	case *types.MyUnionMemberEnumValue:
		_ = v.Value // Value is FooEnum

	case *types.MyUnionMemberListValue:
		_ = v.Value // Value is StringList

	case *types.MyUnionMemberMapValue:
		_ = v.Value // Value is StringMap

	case *types.MyUnionMemberNumberValue:
		_ = v.Value // Value is int32

	case *types.MyUnionMemberStringValue:
		_ = v.Value // Value is string

	case *types.MyUnionMemberStructureValue:
		_ = v.Value // Value is GreetingStruct

	case *types.MyUnionMemberTimestampValue:
		_ = v.Value // Value is Time

	case *types.UnknownUnionMember:
		fmt.Println("unknown tag:", v.Tag)

	default:
		fmt.Println("union is nil or unknown type")

	}
}


text:
@InProceedings{li10b,
  title = {Simple Exponential Family PCA},
  author = {Jun Li and Dacheng Tao},
  pages = {453--460},
  abstract = {Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential principal components (PCs) for data representation.  However, it assumes that data are Gaussian distributed and thus it cannot handle all types of practical observations, e.g. integers and binary values.  In this paper, we propose simple exponential family PCA (SePCA), a generalised family of probabilistic principal component analysers. SePCA employs exponential family distributions to handle general types of observations. By using Bayesian inference, SePCA also automatically discovers the number of essential PCs. We discuss techniques for fitting the model, develop the corresponding mixture model, and show the effectiveness of the model based on experiments.},
  pdf = {http://jmlr.org/proceedings/papers/v9/li10b/li10b.pdf},
}


text:
@InProceedings{Cohan2019Structural,
  author={Arman Cohan and Waleed Ammar and Madeleine Van Zuylen and Field Cady},
  title={Structural Scaffolds for Citation Intent Classification in Scientific Publications},
  booktitle="NAACL",
  year="2019"
}

repository: tensorflow/datasets

repo_name: tensorflow/datasets


text:
#
# base recipe: meta/recipes-bsp/grub/grub_git.bb
# base branch: daisy
#

require grub2.inc

PR = "${INC_PR}.0"

# autogen.sh-exclude-pc:
#	Exclude the .pc from po/POTFILES.in
#	since quilt uses "patch --backup",
# 	which will create the backup file under .pc,
#	this may cause unexpected errors (OE specific).
# grub-2.00-add-oe-kernel.patch:
#	Our kernel's name is bzImage, we need add it to grub.d
#	so grub-mkconfig and grub-install can work correctly (OE specific).
# grub-2.00-fpmath-sse-387-fix.patch:
#	Avoid error: SSE instruction set disabled, using 387 arithmetics [-Werror]
SRC_URI += " \
	file://autogen.sh-exclude-pc.patch \
	file://grub-2.00-add-oe-kernel.patch \
	file://grub-2.00-fpmath-sse-387-fix.patch \
"

DEFAULT_PREFERENCE = "-1"
DEFAULT_PREFERENCE_arm = "1"

COMPATIBLE_HOST = '(x86_64.*|i.86.*|arm.*|aarch64.*)-(linux.*|freebsd.*)'

# configure.ac has code to set this automagically from the target tuple
# but the OE freeform one (core2-foo-bar-linux) don't work with that.

GRUBPLATFORM_arm = "uboot"
GRUBPLATFORM_aarch64 = "efi"
GRUBPLATFORM ??= "pc"

EXTRA_OECONF = "--with-platform=${GRUBPLATFORM} --disable-grub-mkfont --program-prefix='' \
                --enable-liblzma=no --enable-device-mapper=no --enable-libzfs=no"

do_configure_prepend() {
	( cd ${S}
	${S}/autogen.sh )
}

# value for GRUB_CMDLINE_LINUX_DEFAULT in /etc/default/grub
DEFAULT_CMDLINE ?= "quiet"
do_install_append () {
	install -d ${D}${sysconfdir}/default
	sed -i "s/@DEFAULT_CMDLINE@/${DEFAULT_CMDLINE}/g" ${S}/debian/default/grub
	install -m 0644 ${S}/debian/default/grub ${D}${sysconfdir}/default/

	install -d ${D}${sbindir}
	install -m 0755 ${S}/debian/update-grub ${D}${sbindir}
}

# debugedit chokes on bare metal binaries
INHIBIT_PACKAGE_DEBUG_SPLIT = "1"

RDEPENDS_${PN} = "diffutils freetype"
FILES_${PN}-dbg += "${libdir}/${BPN}/*/.debug"

# Sometimes, ELF type of bootloader binary does not match the target architecture,
# bypass check "arch" to avoid the QA error.
INSANE_SKIP_${PN} = "arch"
INSANE_SKIP_${PN}-dbg = "arch"

repository: soderstrom-rikard/meta-debian

repo_name: soderstrom-rikard/meta-debian

branch_name: refs/heads/daisy


text:
@inproceedings{goldstein2016c,
	Address = {Stanford},
	Author = {Goldstein, David M. and Haug, Dag T.\ T.},
	Booksubtitle = {Proceedings of the Joint 2016 Conference on Head-driven Phrase Structure Grammar and Lexical Functional Grammar},
	Booktitle = {Proceedings of {HeadLex}16},
	Date-Added = {2016-10-13 04:06:55 +0000},
	Date-Modified = {2019-08-26 09:17:48 -0700},
	Editor = {Arnold, Doug and Butt, Miriam and Berthold Crysmann and King, Tracy Holloway and Stefan M{\"u}ller},
	Pages = {297--317},
	Publisher = {Center for the Study of Language {a}{n}{d} Information},
	Subtitle = {The case of ancient {Greek}},
	Title = {Second-position clitics and the syntax-phonology interface},
	Url = {http://cslipublications.stanford.edu/HPSG/2016/headlex2016-goldstein-haug.pdf},
	Year = {2016},
	Bdsk-Url-1 = {http://cslipublications.stanford.edu/HPSG/2016/headlex2016-goldstein-haug.pdf}}

repository: DMGoldstein/academic

repo_name: DMGoldstein/academic


text:
include(${CMAKE_TRIPLET_FILE})
if (VCPKG_LIBRARY_LINKAGE STREQUAL static)
    message(FATAL_ERROR "Static building not supported yet")
endif()
include(vcpkg_common_functions)
set(SOURCE_PATH ${CURRENT_BUILDTREES_DIR}/src/glfw-3.2.1)
vcpkg_download_distfile(ARCHIVE
    URLS "https://github.com/glfw/glfw/releases/download/3.2.1/glfw-3.2.1.zip"
    FILENAME "glfw-3.2.1.zip"
    SHA512 73dd6d4a8d28a2b423f0fb25489659c1a845182b7ef09848d4f442cdc489528aea90f43ac84aeedb9d2301c4487f39782b647ee4959e67e83babb838372b980c
)
vcpkg_extract_source_archive(${ARCHIVE})

if(NOT EXISTS ${CURRENT_BUILDTREES_DIR}/patch.stamp)
    file(READ ${SOURCE_PATH}/src/glfw3Config.cmake.in CONFIG)
    string(REPLACE "\"@GLFW_LIB_NAME@\"" "NAMES @GLFW_LIB_NAME@ @GLFW_LIB_NAME@dll"
        CONFIG ${CONFIG}
    )
    string(REPLACE "@PACKAGE_CMAKE_INSTALL_PREFIX@" "@PACKAGE_CMAKE_INSTALL_PREFIX@/../.."
        CONFIG ${CONFIG}
    )
    file(WRITE ${SOURCE_PATH}/src/glfw3Config.cmake.in ${CONFIG})
    file(APPEND ${SOURCE_PATH}/src/glfw3Config.cmake.in "set(GLFW3_LIBRARIES \${GLFW3_LIBRARY})\n")
    file(WRITE ${CURRENT_BUILDTREES_DIR}/patch.stamp)
endif()

vcpkg_configure_cmake(
    SOURCE_PATH ${SOURCE_PATH}
    OPTIONS
        -DBUILD_SHARED_LIBS=ON
        -DGLFW_BUILD_EXAMPLES=OFF
        -DGLFW_BUILD_TESTS=OFF
        -DGLFW_BUILD_DOCS=OFF
        -DPACKAGE_CMAKE_INSTALL_PREFIX=\${CMAKE_CURRENT_LIST_DIR}/../..
    # OPTIONS_RELEASE -DOPTIMIZE=1
    # OPTIONS_DEBUG -DDEBUGGABLE=1
)

vcpkg_install_cmake()

file(MAKE_DIRECTORY
    ${CURRENT_PACKAGES_DIR}/bin
    ${CURRENT_PACKAGES_DIR}/debug/bin
    ${CURRENT_PACKAGES_DIR}/share
)
file(RENAME ${CURRENT_PACKAGES_DIR}/lib/glfw3.dll ${CURRENT_PACKAGES_DIR}/bin/glfw3.dll)
file(RENAME ${CURRENT_PACKAGES_DIR}/debug/lib/glfw3.dll ${CURRENT_PACKAGES_DIR}/debug/bin/glfw3.dll)

file(RENAME ${CURRENT_PACKAGES_DIR}/lib/cmake/glfw3 ${CURRENT_PACKAGES_DIR}/share/glfw3)
file(REMOVE_RECURSE ${CURRENT_PACKAGES_DIR}/lib/cmake)
file(RENAME ${CURRENT_PACKAGES_DIR}/debug/lib/cmake/glfw3/glfw3Targets-debug.cmake ${CURRENT_PACKAGES_DIR}/share/glfw3/glfw3Targets-debug.cmake)
file(REMOVE_RECURSE ${CURRENT_PACKAGES_DIR}/debug/lib/cmake)

file(REMOVE_RECURSE ${CURRENT_PACKAGES_DIR}/debug/include)

file(REMOVE ${CURRENT_PACKAGES_DIR}/lib/glfw3.lib)
file(REMOVE ${CURRENT_PACKAGES_DIR}/debug/lib/glfw3.lib)

file(COPY ${SOURCE_PATH}/COPYING.txt DESTINATION ${CURRENT_PACKAGES_DIR}/share/glfw3)
file(RENAME ${CURRENT_PACKAGES_DIR}/share/glfw3/COPYING.txt ${CURRENT_PACKAGES_DIR}/share/glfw3/copyright)
vcpkg_copy_pdbs()


text:
@misc{broman-2013,
  annote = {Dr. Broman offers practical advice on listening, admitting when you don't know the answer, and how to say no.},
  author = {Kenneth Broman},
  mendeley-tags = {Human side of statistics},
  title = {Thoughts on statistical consulting, The stupidest thing blog, 2013-04-02},
  source = {19/06/broman-2013},
  url = {https://kbroman.wordpress.com/2013/04/02/thoughts-on-statistical-consulting/},
  urldate = {2019-06-03}
}

repository: pmean/build-website

repo_name: pmean/build-website


text:
@ARTICLE {OCT2017,
    author  = "Bertsimas, Dimitris and Dunn, Jack",
    title   = "Optimal classification trees",
    journal = "Machine Learning",
    year    = "2017",
    volume  = "106",
    number  = "7",
    pages   = "1039-1082",
    url     = "https://doi.org/10.1007/s10994-017-5633-9"
}
@BOOK {IMD2004,
    author    = "Hernández Orallo, José and Ramírez Quintana, José and Ferri Ramírez, César",
    title     = "Introducción a la Minería de Datos",
    publisher = "Pearson Prentice Hall",
    year      = "2004",
    ISBN      = "9788483225585"
}
@BOOK {IOR2015,
    author    = "Hillier, Frederick S. and Lieberman, Gerald J.",
    title     = "Introduction to Operations Research",
    publisher = "McGraw-Hill Education",
    year      = "2015",
    edition   = "tenth"
}
@BOOK {ESL2009,
    author    = "Hastie, Trevor and Tibshirani, Robert and Friedman, Jerome",
    title     = "The Elements of Statistical Learning",
    publisher = "Springer-Verlag New York",
    year      = "2009",
    series    = "Springer Series in Statistics",
    edition   = "second",
    doi       = "10.1007/978-0-387-84858-7",
    ISBN      = "9780387848587"
}

license: Unlicense,MIT

repository: AndresAlb/Proyectos-ITAM

detected_licenses: Unlicense MIT

repo_name: AndresAlb/Proyectos-ITAM


text:
@article{DBLP:journals/cse/Laufer05,
 author = {Konstantin Läufer},
 bibsource = {dblp computer science bibliography, https://dblp.org},
 biburl = {https://dblp.org/rec/journals/cse/Laufer05.bib},
 doi = {10.1109/MCSE.2005.85},
 journal = {Comput. Sci. Eng.},
 number = {5},
 pages = {80--88},
 timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
 title = {A hike through post-EJB J2EE Web application architecture},
 url = {https://doi.org/10.1109/MCSE.2005.85},
 volume = {7},
 year = {2005}
}


text:
package model

// Choice between a reason or no reason for the corporate action instruction or instruction cancellation cancelled/cancellation completed status.
type CancelledStatus14Choice struct {

	// Reason not specified.
	NoSpecifiedReason *NoReasonCode `xml:"NoSpcfdRsn"`

	// Reason for the cancelled status.
	Reason []*CancelledStatusReason13 `xml:"Rsn"`
}

func (c *CancelledStatus14Choice) SetNoSpecifiedReason(value string) {
	c.NoSpecifiedReason = (*NoReasonCode)(&value)
}

func (c *CancelledStatus14Choice) AddReason() *CancelledStatusReason13 {
	newValue := new(CancelledStatusReason13)
	c.Reason = append(c.Reason, newValue)
	return newValue
}


text:
@ARTICLE{2021ApJ...910..145P,
       author = {{Pereira}, Jonas P. and {Bejger}, Micha{\l} and {Tonetto}, Lucas and {Lugones}, Germ{\'a}n and {Haensel}, Pawe{\l} and {Zdunik}, Julian Leszek and {Sieniawska}, Magdalena},
        title = "{Probing Elastic Quark Phases in Hybrid Stars with Radius Measurements}",
      journal = {\apj},
     keywords = {General relativity, Neutron stars, Stellar oscillations, 641, 1108, 1617, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
         year = 2021,
        month = apr,
       volume = {910},
       number = {2},
          eid = {145},
        pages = {145},
          doi = {10.3847/1538-4357/abe633},
archivePrefix = {arXiv},
       eprint = {2011.06361},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021ApJ...910..145P},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2021arXiv210307688M,
       author = {{Morawski}, Filip and {Bejger}, Micha{\l} and {Cuoco}, Elena and {Petre}, Luigia},
        title = "{Anomaly Detection in Gravitational Waves data using Convolutional AutoEncoders}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology},
         year = 2021,
        month = mar,
          eid = {arXiv:2103.07688},
        pages = {arXiv:2103.07688},
archivePrefix = {arXiv},
       eprint = {2103.07688},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv210307688M},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2020MNRAS.498.4605H,
       author = {{Ho}, Wynn C.~G. and {Espinoza}, Crist{\'o}bal M. and {Arzoumanian}, Zaven and {Enoto}, Teruaki and {Tamba}, Tsubasa and {Antonopoulou}, Danai and {Bejger}, Micha{\l} and {Guillot}, Sebastien and {Haskell}, Brynmor and {Ray}, Paul S.},
        title = "{Return of the Big Glitcher: NICER timing and glitches of PSR J0537-6910}",
      journal = {\mnras},
     keywords = {gravitational waves, stars: neutron, pulsars: individual: PSR J0537-6910, X-rays: individual: PSR J0537-6910, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics, General Relativity and Quantum Cosmology},
         year = 2020,
        month = nov,
       volume = {498},
       number = {4},
        pages = {4605-4614},
          doi = {10.1093/mnras/staa2640},
archivePrefix = {arXiv},
       eprint = {2009.00030},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.4605H},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2020A&A...642A..78M,
       author = {{Morawski}, F. and {Bejger}, M.},
        title = "{Neural network reconstruction of the dense matter equation of state derived from the parameters of neutron stars}",
      journal = {\aap},
     keywords = {equation of state, dense matter, stars: neutron, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = 2020,
        month = oct,
       volume = {642},
          eid = {A78},
        pages = {A78},
          doi = {10.1051/0004-6361/202038130},
archivePrefix = {arXiv},
       eprint = {2006.07194},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020A&A...642A..78M},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2020arXiv200503745C,
       author = {{Cuoco}, Elena and {Powell}, Jade and {Cavagli{\`a}}, Marco and {Ackley}, Kendall and {Bejger}, Michal and others},
        title = "{Enhancing Gravitational-Wave Science with Machine Learning}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
         year = 2020,
        month = may,
          eid = {arXiv:2005.03745},
        pages = {arXiv:2005.03745},
archivePrefix = {arXiv},
       eprint = {2005.03745},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020arXiv200503745C},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2020ApJ...895...28P,
       author = {{Pereira}, Jonas P. and {Bejger}, Micha{\l} and {Andersson}, Nils and {Gittins}, Fabian},
        title = "{Tidal Deformations of Hybrid Stars with Sharp Phase Transitions and Elastic Crusts}",
      journal = {\apj},
     keywords = {General relativity, Neutron stars, Gravitational waves, 641, 1108, 678, General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics},
         year = 2020,
        month = may,
       volume = {895},
       number = {1},
          eid = {28},
        pages = {28},
          doi = {10.3847/1538-4357/ab8aca},
archivePrefix = {arXiv},
       eprint = {2003.10781},
 primaryClass = {gr-qc},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020ApJ...895...28P},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2019A&A...622A.174S,
       author = {{Sieniawska}, M. and {Turcza{\'n}ski}, W. and {Bejger}, M. and {Zdunik}, J.~L.},
        title = "{Tidal deformability and other global parameters of compact stars with strong phase transitions}",
      journal = {\aap},
     keywords = {stars: neutron, equation of state, dense matter, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
         year = 2019,
        month = feb,
       volume = {622},
          eid = {A174},
        pages = {A174},
          doi = {10.1051/0004-6361/201833969},
archivePrefix = {arXiv},
       eprint = {1807.11581},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019A&A...622A.174S},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2021arXiv210414417T,
       author = {{Abbott}, R. and others},
        title = "{Constraints from LIGO O3 data on gravitational-wave emission due to r-modes in the glitching pulsar PSR J0537-6910}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
         year = 2021,
        month = apr,
          eid = {arXiv:2104.14417},
        pages = {arXiv:2104.14417},
archivePrefix = {arXiv},
       eprint = {2104.14417},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv210414417T},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

%@ARTICLE{2020ApJ...892L...3A,
%       author = {{Abbott}, B.~P. and others},
%        title = "{GW190425: Observation of a Compact Binary Coalescence with Total Mass ${\sim}3.4 M_\odot$}",
%      journal = {\apjl},
%     keywords = {Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
%         year = 2020,
%        month = mar,
%       volume = {892},
%       number = {1},
%          eid = {L3},
%        pages = {L3},
%          doi = {10.3847/2041-8213/ab75f5},
%archivePrefix = {arXiv},
%       eprint = {2001.01761},
% primaryClass = {astro-ph.HE},
%       adsurl = {https://ui.adsabs.harvard.edu/abs/2020ApJ...892L...3A},
%      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

@ARTICLE{2020arXiv200503745C,
       author = {{Cuoco}, Elena and {Powell}, Jade and {Cavagli{\`a}}, Marco and
         {Ackley}, Kendall and {Bejger}, Michal and others},
        title = "{Enhancing Gravitational-Wave Science with Machine Learning}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
         year = 2020,
        month = may,
          eid = {arXiv:2005.03745},
        pages = {arXiv:2005.03745},
archivePrefix = {arXiv},
       eprint = {2005.03745},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020arXiv200503745C},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2020ApJ...895...28P,
       author = {{Pereira}, Jonas P. and {Bejger}, Micha{\l} and {Andersson}, Nils and
         {Gittins}, Fabian},
        title = "{Tidal Deformations of Hybrid Stars with Sharp Phase Transitions and Elastic Crusts}",
      journal = {\apj},
     keywords = {General relativity, Neutron stars, Gravitational waves, General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics},
         year = 2020,
        month = may,
       volume = {895},
       number = {1},
          eid = {28},
        pages = {28},
          doi = {10.3847/1538-4357/ab8aca},
archivePrefix = {arXiv},
       eprint = {2003.10781},
 primaryClass = {gr-qc},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020ApJ...895...28P},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2019Univ....5..217S,
       author = {{Sieniawska}, Magdalena and {Bejger}, Micha{\l}},
        title = "{Continuous Gravitational Waves from Neutron Stars: Current Status and Prospects}",
      journal = {Universe},
     keywords = {Astrophysics - High Energy Astrophysical Phenomena},
         year = 2019,
        month = oct,
       volume = {5},
       number = {11},
        pages = {217},
          doi = {10.3390/universe5110217},
archivePrefix = {arXiv},
       eprint = {1909.12600},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019Univ....5..217S},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2018ApJ...868...17A,
       author = {{Abramowicz}, Marek A. and {Bejger}, Micha{\l} and {Wielgus}, Maciek},
        title = "{Collisions of Neutron Stars with Primordial Black Holes as Fast Radio Bursts Engines}",
      journal = {\apj},
     keywords = {black hole physics, dark matter, stars: neutron, Astrophysics - High Energy Astrophysical Phenomena},
         year = 2018,
        month = nov,
       volume = {868},
       number = {1},
          eid = {17},
        pages = {17},
          doi = {10.3847/1538-4357/aae64a},
archivePrefix = {arXiv},
       eprint = {1704.05931},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2018ApJ...868...17A},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

%@ARTICLE{2019arXiv190513488S,
%       author = {{Sieniawska}, Magdalena and {Bejger}, Micha{\l} and
%         {Kr{\'o}lak}, Andrzej},
%        title = "{Follow-up procedure for gravitational wave searches from isolated neutron stars using the time-domain $\mathcal{F}$-statistic method}",
%      journal = {arXiv e-prints},
%     keywords = {Astrophysics - Instrumentation and Methods for Astrophysics},
%         year = "2019",
%        month = "May",
%          eid = {arXiv:1905.13488},
%        pages = {arXiv:1905.13488},
%archivePrefix = {arXiv},
%       eprint = {1905.13488},
% primaryClass = {astro-ph.IM},
%       adsurl = {https://ui.adsabs.harvard.edu/abs/2019arXiv190513488S},
%      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2019A&A...622A.174S,
%       author = {{Sieniawska}, M. and {Turczanski}, W. and {Bejger}, M. and
%         {Zdunik}, J.~L.},
%        title = "{Tidal deformability and other global parameters of compact stars with strong phase transitions}",
%      journal = {\aap},
%     keywords = {stars: neutron, equation of state, dense matter, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
%         year = "2019",
%        month = "Feb",
%       volume = {622},
%          eid = {A174},
%        pages = {A174},
%          doi = {10.1051/0004-6361/201833969},
%archivePrefix = {arXiv},
%       eprint = {1807.11581},
% primaryClass = {astro-ph.HE},
%       adsurl = {https://ui.adsabs.harvard.edu/abs/2019A&A...622A.174S},
%      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2018SSRv..214...32C,
%   author = {{Czerny}, B. and {Beaton}, R. and {Bejger}, M. and {Cackett}, E. and
%  {Dall'Ora}, M. and {Holanda}, R.~F.~L. and {Jensen}, J.~B. and
%  {Jha}, S.~W. and {Lusso}, E. and {Minezaki}, T. and {Risaliti}, G. and
%  {Salaris}, M. and {Toonen}, S. and {Yoshii}, Y.},
%    title = "{Astronomical Distance Determination in the Space Age. Secondary Distance Indicators}",
%  journal = {\ssr},
%archivePrefix = "arXiv",
%   eprint = {1801.00598},
% keywords = {Distance scale, Galaxies: distances and redshifts, Stars: supernovae},
%     year = 2018,
%    month = feb,
%   volume = 214,
%      eid = {32},
%    pages = {32},
%      doi = {10.1007/s11214-018-0466-9},
%   adsurl = {http://adsabs.harvard.edu/abs/2018SSRv..214...32C},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2018ApJ...868...17A,
%   author = {{Abramowicz}, M.~A. and {Bejger}, M. and {Wielgus}, M.},
%    title = "{Collisions of Neutron Stars with Primordial Black Holes as Fast Radio Bursts Engines}",
%  journal = {\apj},
%archivePrefix = "arXiv",
%   eprint = {1704.05931},
% primaryClass = "astro-ph.HE",
% keywords = {black hole physics, dark matter, stars: neutron },
%     year = 2018,
%    month = nov,
%   volume = 868,
%      eid = {17},
%    pages = {17},
%      doi = {10.3847/1538-4357/aae64a},
%   adsurl = {http://adsabs.harvard.edu/abs/2018ApJ...868...17A},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2017PhRvD..96f2002A,
%   author = {{Abbott}, B.~P. and {Abbott}, R. and {Abbott}, T.~D. and {Acernese}, F. and
%  {Ackley}, K. and {Adams}, C. and {Adams}, T. and {Addesso}, P. and
%  {Adhikari}, R.~X. and {Adya}, V.~B. and et al.},
%    title = "{All-sky search for periodic gravitational waves in the O1 LIGO data}",
%  journal = {\prd},
%archivePrefix = "arXiv",
%   eprint = {1707.02667},
% primaryClass = "gr-qc",
%     year = 2017,
%    month = sep,
%   volume = 96,
%   number = 6,
%      eid = {062002},
%    pages = {062002},
%      doi = {10.1103/PhysRevD.96.062002},
%   adsurl = {http://adsabs.harvard.edu/abs/2017PhRvD..96f2002A},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2018ApJ...855..116V,
%   author = {{Vincent}, F.~H. and {Bejger}, M. and {Rozanska}, A. and
%  {Straub}, O. and {Paumard}, T. and {Fortin}, M. and {Madej}, J. and
%  {Majczyna}, A. and {Gourgoulhon}, E. and {Haensel}, P. and {Zdunik}, L. and
%  {Beldycki}, B.},
%    title = "{Accurate Ray-tracing of Realistic Neutron Star Atmospheres for Constraining Their Parameters}",
%  journal = {\apj},
%archivePrefix = "arXiv",
%   eprint = {1711.02414},
% primaryClass = "astro-ph.HE",
% keywords = {equation of state, gravitation, radiative transfer, relativistic processes, stars: neutron },
%     year = 2018,
%    month = mar,
%   volume = 855,
%      eid = {116},
%    pages = {116},
%      doi = {10.3847/1538-4357/aab0a3},
%   adsurl = {http://adsabs.harvard.edu/abs/2018ApJ...855..116V},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2019PhRvD.100b4004A,
%       author = {{Abbott}, B.~P. and {Abbott}, R. and {Abbott}, T.~D. and {Abraham}, S. and
%         {Acernese}, F. and {Ackley}, K. and {Adams}, C. and {Adhikari}, R.~X. and
%         {Adya}, V.~B. and {Affeldt}, C. and et al.},
%        title = "{All-sky search for continuous gravitational waves from isolated neutron stars using Advanced LIGO O2 data}",
%      journal = {\prd},
%     keywords = {Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology},
%         year = "2019",
%        month = "Jul",
%       volume = {100},
%       number = {2},
%          eid = {024004},
%        pages = {024004},
%          doi = {10.1103/PhysRevD.100.024004},
%archivePrefix = {arXiv},
%       eprint = {1903.01901},
% primaryClass = {astro-ph.HE},
%       adsurl = {https://ui.adsabs.harvard.edu/abs/2019PhRvD.100b4004A},
%      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2017PhRvL.119p1101A,
%   author = {{Abbott}, B.~P. and {Abbott}, R. and {Abbott}, T.~D. and {Acernese}, F. and
%  {Ackley}, K. and {Adams}, C. and {Adams}, T. and {Addesso}, P. and
%  {Adhikari}, R.~X. and {Adya}, V.~B. and et al.},
%    title = "{GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral}",
%  journal = {Physical Review Letters},
%archivePrefix = "arXiv",
%   eprint = {1710.05832},
% primaryClass = "gr-qc",
%     year = 2017,
%    month = oct,
%   volume = 119,
%   number = 16,
%      eid = {161101},
%    pages = {161101},
%      doi = {10.1103/PhysRevLett.119.161101},
%   adsurl = {http://adsabs.harvard.edu/abs/2017PhRvL.119p1101A},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2017arXiv171006607B,
%   author = {{Bejger}, M.},
%    title = "{Status of the continuous GW searches in the Advanced Detector Era}",
%  journal = {Rencontres de Moriond 2017, Gravitation session},
%archivePrefix = "arXiv",
%   eprint = {arXiv:1710.06607},
% primaryClass = "gr-qc",
% keywords = {General Relativity and Quantum Cosmology},
%     year = 2017,
%    month = oct,
%   adsurl = {http://adsabs.harvard.edu/abs/2017arXiv171006607B},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2017NewA...51....7J,
%   author = {{Janiuk}, A. and {Bejger}, M. and {Charzynski}, S. and {Sukova}, P.
%  },
%    title = "{On the possible gamma-ray burst-gravitational wave association in GW150914}",
%  journal = {\na},
%archivePrefix = "arXiv",
%   eprint = {1604.07132},
% primaryClass = "astro-ph.HE",
% keywords = {Black hole physics, Accretion, Accretion disks, Gravitational waves, Neutrinos},
%     year = 2017,
%    month = feb,
%   volume = 51,
%    pages = {7-14},
%      doi = {10.1016/j.newast.2016.08.002},
%   adsurl = {http://adsabs.harvard.edu/abs/2017NewA...51....7J},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2018A&A...616A.105S,
%   author = {{Sieniawska}, M. and {Bejger}, M. and {Haskell}, B.},
%    title = "{Estimating the equation of state from measurements of neutron star radii with 5\% accuracy}",
%  journal = {\aap},
% keywords = {equation of state, dense matter, stars: neutron},
%     year = 2018,
%    month = aug,
%   volume = 616,
%      eid = {A105},
%    pages = {A105},
%      doi = {10.1051/0004-6361/201833071},
%   adsurl = {http://adsabs.harvard.edu/abs/2018A%26A...616A.105S},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System},
%  journal = {ArXiv e-prints},
%archivePrefix = "arXiv",
%   eprint = {1803.08813},
% primaryClass = "astro-ph.HE",
%}

%@ARTICLE{2017ApJ...839...12A,
%   author = {{Abbott}, B.~P. and {Abbott}, R. and {Abbott}, T.~D. and {Abernathy}, M.~R. and
%  {Acernese}, F. and {Ackley}, K. and {Adams}, C. and {Adams}, T. and
%  {Addesso}, P. and {Adhikari}, R.~X. and et al.},
%    title = "{First Search for Gravitational Waves from Known Pulsars with Advanced LIGO}",
%  journal = {\apj},
%archivePrefix = "arXiv",
%   eprint = {1701.07709},
% primaryClass = "astro-ph.HE",
% keywords = {gravitational waves, pulsars: general},
%     year = 2017,
%    month = apr,
%   volume = 839,
%      eid = {12},
%    pages = {12},
%      doi = {10.3847/1538-4357/aa677f},
%   adsurl = {http://adsabs.harvard.edu/abs/2017ApJ...839...12A},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}
%

%@ARTICLE{2016PhRvD..94l4010W,
%   author = {{Walsh}, S. and {Pitkin}, M. and {Oliver}, M. and {D'Antonio}, S. and
%  {Dergachev}, V. and {Kr{\'o}lak}, A. and {Astone}, P. and {Bejger}, M. and
%  {Di Giovanni}, M. and {Dorosh}, O. and et al.},
%    title = "{Comparison of methods for the detection of gravitational waves from unknown neutron stars}",
%  journal = {\prd},
%archivePrefix = "arXiv",
%   eprint = {1606.00660},
% primaryClass = "gr-qc",
%     year = 2016,
%    month = dec,
%   volume = 94,
%   number = 12,
%      eid = {124010},
%    pages = {124010},
%      doi = {10.1103/PhysRevD.94.124010},
%   adsurl = {http://adsabs.harvard.edu/abs/2016PhRvD..94l4010W},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}
%
%@ARTICLE{2017A&A...600A..39B,
%   author = {{Bejger}, M. and {Blaschke}, D. and {Haensel}, P. and {Zdunik}, J.~L. and
%  {Fortin}, M.},
%    title = "{Consequences of a strong phase transition in the dense matter equation of state for the rotational evolution of neutron stars}",
%  journal = {\aap},
%archivePrefix = "arXiv",
%   eprint = {1608.07049},
% primaryClass = "astro-ph.HE",
% keywords = {stars: neutron, equation of state, pulsars: general},
%     year = 2017,
%    month = apr,
%   volume = 600,
%      eid = {A39},
%    pages = {A39},
%      doi = {10.1051/0004-6361/201629580},
%   adsurl = {http://adsabs.harvard.edu/abs/2017A%26A...600A..39B},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}

%@ARTICLE{2017PhRvL.119n1101A,
%   author = {{Abbott}, B.~P. and {Abbott}, R. and {Abbott}, T.~D. and {Acernese}, F. and
%  {Ackley}, K. and {Adams}, C. and {Adams}, T. and {Addesso}, P. and
%  {Adhikari}, R.~X. and {Adya}, V.~B. and et al.},
%    title = "{GW170814: A Three-Detector Observation of Gravitational Waves from a Binary Black Hole Coalescence}",
%  journal = {Physical Review Letters},
%archivePrefix = "arXiv",
%   eprint = {1709.09660},
% primaryClass = "gr-qc",
%     year = 2017,
%    month = oct,
%   volume = 119,
%   number = 14,
%      eid = {141101},
%    pages = {141101},
%      doi = {10.1103/PhysRevLett.119.141101},
%   adsurl = {http://adsabs.harvard.edu/abs/2017PhRvL.119n1101A},
%  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
%}


text:
// Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT.

package codestarconnections

import (
	"context"

	"github.com/aws/aws-sdk-go-v2/aws"
	"github.com/aws/aws-sdk-go-v2/internal/awsutil"
)

type DeleteHostInput struct {
	_ struct{} `type:"structure"`

	// The Amazon Resource Name (ARN) of the host to be deleted.
	//
	// HostArn is a required field
	HostArn *string `type:"string" required:"true"`
}

// String returns the string representation
func (s DeleteHostInput) String() string {
	return awsutil.Prettify(s)
}

// Validate inspects the fields of the type to determine if they are valid.
func (s *DeleteHostInput) Validate() error {
	invalidParams := aws.ErrInvalidParams{Context: "DeleteHostInput"}

	if s.HostArn == nil {
		invalidParams.Add(aws.NewErrParamRequired("HostArn"))
	}

	if invalidParams.Len() > 0 {
		return invalidParams
	}
	return nil
}

type DeleteHostOutput struct {
	_ struct{} `type:"structure"`
}

// String returns the string representation
func (s DeleteHostOutput) String() string {
	return awsutil.Prettify(s)
}

const opDeleteHost = "DeleteHost"

// DeleteHostRequest returns a request value for making API operation for
// AWS CodeStar connections.
//
// The host to be deleted. Before you delete a host, all connections associated
// to the host must be deleted.
//
// A host cannot be deleted if it is in the VPC_CONFIG_INITIALIZING or VPC_CONFIG_DELETING
// state.
//
//    // Example sending a request using DeleteHostRequest.
//    req := client.DeleteHostRequest(params)
//    resp, err := req.Send(context.TODO())
//    if err == nil {
//        fmt.Println(resp)
//    }
//
// Please also see https://docs.aws.amazon.com/goto/WebAPI/codestar-connections-2019-12-01/DeleteHost
func (c *Client) DeleteHostRequest(input *DeleteHostInput) DeleteHostRequest {
	op := &aws.Operation{
		Name:       opDeleteHost,
		HTTPMethod: "POST",
		HTTPPath:   "/",
	}

	if input == nil {
		input = &DeleteHostInput{}
	}

	req := c.newRequest(op, input, &DeleteHostOutput{})

	return DeleteHostRequest{Request: req, Input: input, Copy: c.DeleteHostRequest}
}

// DeleteHostRequest is the request type for the
// DeleteHost API operation.
type DeleteHostRequest struct {
	*aws.Request
	Input *DeleteHostInput
	Copy  func(*DeleteHostInput) DeleteHostRequest
}

// Send marshals and sends the DeleteHost API request.
func (r DeleteHostRequest) Send(ctx context.Context) (*DeleteHostResponse, error) {
	r.Request.SetContext(ctx)
	err := r.Request.Send()
	if err != nil {
		return nil, err
	}

	resp := &DeleteHostResponse{
		DeleteHostOutput: r.Request.Data.(*DeleteHostOutput),
		response:         &aws.Response{Request: r.Request},
	}

	return resp, nil
}

// DeleteHostResponse is the response type for the
// DeleteHost API operation.
type DeleteHostResponse struct {
	*DeleteHostOutput

	response *aws.Response
}

// SDKResponseMetdata returns the response metadata for the
// DeleteHost request.
func (r *DeleteHostResponse) SDKResponseMetdata() *aws.Response {
	return r.response
}