289 citations · 309 across the 7 of their papers we have counts for
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cs.SD2020★ 11 cited
Towards Listening to 10 People Simultaneously: An Efficient Permutation Invariant Training of Audio Source Separation Using Sinkhorn's Algorithm
Hideyuki Tachibana
In neural network-based monaural speech separation techniques, it has been recently common to evaluate the loss using the permutation invariant training (PIT) loss. However, the or…
cs.SD2017★ 289 cited
Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention
Hideyuki Tachibana, Katsuya Uenoyama, Shunsuke Aihara
This paper describes a novel text-to-speech (TTS) technique based on deep convolutional neural networks (CNN), without use of any recurrent units. Recurrent neural networks (RNN) h…