222 citations · 359 across the 3 of their papers we have counts for
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cs.CL2017★ 71 cited
Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks
Ying Zhang, Mohammad Pezeshki, Philemon Brakel +3
Convolutional Neural Networks (CNNs) are effective models for reducing spectral variations and modeling spectral correlations in acoustic features for automatic speech recognition…
cs.CL2016★ 66 cited
Invariant Representations for Noisy Speech Recognition
Dmitriy Serdyuk, Kartik Audhkhasi, Philémon Brakel +3
Modern automatic speech recognition (ASR) systems need to be robust under acoustic variability arising from environmental, speaker, channel, and recording conditions. Ensuring such…