title: IIITH-CSTD Corpus: Crowdsourced Strategies for the Collection of a Large-scale Telugu Speech Corpus
abstract: Due to the lack of a large annotated speech corpus, many low-resource Indian languages struggle to utilize recent advancements in deep neural network architectures for Automatic Speech Recognition (ASR) tasks. Collecting large-scale databases is an expensive and time-consuming task. Current approaches lack extensive traditional expert-based data acquisition guidelines, as they are tedious and complex. In this work, we present the International Institute of Information Technology Hyderabad-Crowd 
journal: ACM Transactions on Asian and Low-Resource Language Information Processing