106 citations · 212 across the 9 of their papers we have counts for
5 papers · 1 filter
Speech recognition with quaternion neural networks
Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid +2
Neural network architectures are at the core of powerful automatic speech recognition systems (ASR). However, while recent researches focus on novel model architectures, the acoust…
Bidirectional Quaternion Long-Short Term Memory Recurrent Neural Networks for Speech Recognition
Titouan Parcollet, Mohamed Morchid, Georges Linarès +1
Recurrent neural networks (RNN) are at the core of modern automatic speech recognition (ASR) systems. In particular, long-short term memory (LSTM) recurrent neural networks have ac…
Quaternion Convolutional Neural Networks for Heterogeneous Image Processing
Titouan Parcollet, Mohamed Morchid, Georges Linarès
Convolutional neural networks (CNN) have recently achieved state-of-the-art results in various applications. In the case of image recognition, an ideal model has to learn independe…
Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition
Titouan Parcollet, Ying Zhang, Mohamed Morchid +4
Recently, the connectionist temporal classification (CTC) model coupled with recurrent (RNN) or convolutional neural networks (CNN), made it easier to train speech recognition syst…
Quaternion Recurrent Neural Networks
Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid +4
Recurrent neural networks (RNNs) are powerful architectures to model sequential data, due to their capability to learn short and long-term dependencies between the basic elements o…