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Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition
2018
Interspeech 2018
Recently, the connectionist temporal classification (CTC) model coupled with recurrent (RNN) or convolutional neural networks (CNN), made it easier to train speech recognition systems in an end-to-end fashion. However in real-valued models, time frame components such as mel-filter-bank energies and the cepstral coefficients obtained from them, together with their first and second order derivatives, are processed as individual elements, while a natural alternative is to process such components
doi:10.21437/interspeech.2018-1898
dblp:conf/interspeech/ParcolletZMTLMB18
fatcat:4pykru2h2raelk7osfng6kylme