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Found 6 papers, 3 papers with code
Adversarial Joint Training with Self-Attention Mechanism for Robust End-to-End Speech Recognition
Inspired by the extensive applications of the generative adversarial networks (GANs) in speech enhancement and ASR tasks, we propose an adversarial joint training framework with the self-attention mechanism to boost the noise robustness of the ASR system.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Lightweight End-to-End Speech Recognition from Raw Audio Data Using Sinc-Convolutions
For this, we propose Lightweight Sinc-Convolutions (LSC) that integrate Sinc-convolutions with depthwise convolutions as a low-parameter machine-learnable feature extraction for end-to-end ASR systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
MP3 Compression To Diminish Adversarial Noise in End-to-End Speech Recognition
The present work proposes MP3 compression as a means to decrease the impact of Adversarial Noise (AN) in audio samples transcribed by ASR systems.
Audio and Speech Processing Cryptography and Security Sound
CTC-Segmentation of Large Corpora for German End-to-end Speech Recognition
In this work, we combine freely available corpora for German speech recognition, including yet unlabeled speech data, to a big dataset of over $1700$h of speech data.
Ranked #5 on
Speech Recognition
on TUDA
(using extra training data)
Speech Recognition
Audio and Speech Processing
Regularized Forward-Backward Decoder for Attention Models
Nowadays, attention models are one of the popular candidates for speech recognition.
Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions
Keyword Spotting (KWS) enables speech-based user interaction on smart devices.
