419 citations · 966 across the 15 of their papers we have counts for
5 papers · 1 filter
Learning Independent Features with Adversarial Nets for Non-linear ICA
Philemon Brakel, Yoshua Bengio
Reliable measures of statistical dependence could be useful tools for learning independent features and performing tasks like source separation using Independent Component Analysis…
Improving speech recognition by revising gated recurrent units
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Speech recognition is largely taking advantage of deep learning, showing that substantial benefits can be obtained by modern Recurrent Neural Networks (RNNs). The most popular RNNs…
Batch-normalized joint training for DNN-based distant speech recognition
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Improving distant speech recognition is a crucial step towards flexible human-machine interfaces. Current technology, however, still exhibits a lack of robustness, especially when…
A network of deep neural networks for distant speech recognition
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Despite the remarkable progress recently made in distant speech recognition, state-of-the-art technology still suffers from a lack of robustness, especially when adverse acoustic c…
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…