title: MP3 Compression as a Means to Improve Robustness against Adversarial Noise Targeting Attention-based End-to-End Speech Recognition
abstract: Adversarial Examples represent an imminent security threat to any Machine Learning system.The present thesis addresses this issue by proposing MP3-compression as a potential measure to reduce the susceptibility of Automatic Speech Recognition (ASR) systems to be mislead by Audio Adversarial Examples (AAEs).In essence, we used the Fast Gradient Sign Method (FGSM) to generate untargeted AAEs in the form of adversarial noise added to original speech samples.We used a feature inversion procedure to 
journal: mediaTUM  (Technical University of Munich)