79 citations · 144 across the 9 of their papers we have counts for
7 papers · 1 filter
Adversarial Joint Training with Self-Attention Mechanism for Robust End-to-End Speech Recognition
Lujun Li, Yikai Kang, Yuchen Shi +3
Lately, the self-attention mechanism has marked a new milestone in the field of automatic speech recognition (ASR). Nevertheless, its performance is susceptible to environmental in…
Lightweight End-to-End Speech Recognition from Raw Audio Data Using Sinc-Convolutions
Ludwig Kürzinger, Nicolas Lindae, Palle Klewitz +1
Many end-to-end Automatic Speech Recognition (ASR) systems still rely on pre-processed frequency-domain features that are handcrafted to emulate the human hearing. Our work is moti…
MP3 Compression To Diminish Adversarial Noise in End-to-End Speech Recognition
Iustina Andronic, Ludwig Kürzinger, Edgar Ricardo Chavez Rosas +2
Audio Adversarial Examples (AAE) represent specially created inputs meant to trick Automatic Speech Recognition (ASR) systems into misclassification. The present work proposes MP3…
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition
Ludwig Kürzinger, Edgar Ricardo Chavez Rosas, Lujun Li +2
Recent advances in Automatic Speech Recognition (ASR) demonstrated how end-to-end systems are able to achieve state-of-the-art performance. There is a trend towards deeper neural n…
CTC-Segmentation of Large Corpora for German End-to-end Speech Recognition
Ludwig Kürzinger, Dominik Winkelbauer, Lujun Li +2
Recent end-to-end Automatic Speech Recognition (ASR) systems demonstrated the ability to outperform conventional hybrid DNN/ HMM ASR. Aside from architectural improvements in those…
Regularized Forward-Backward Decoder for Attention Models
Tobias Watzel, Ludwig Kürzinger, Lujun Li +1
Nowadays, attention models are one of the popular candidates for speech recognition. So far, many studies mainly focus on the encoder structure or the attention module to enhance t…