Shinji Watanabe

The third ‘CHiME’ speech separation and recognition challenge: Dataset, task and baselines

Jon Barker, Ricard Marxer, Emmanuel Vincent, Shinji Watanabe
IEEE Workshop on Automatic Speech Recognition and…
2015

The CHiME challenge series aims to advance far field speech recognition technology by promoting research at the interface of signal processing and automatic speech recognition. This paper presents… (More)

Deep clustering: Discriminative embeddings for segmentation and separation

John R. Hershey, Zhuo Chen, Jonathan Le Roux, Shinji Watanabe
IEEE International Conference on Acoustics…
2016

We address the problem of "cocktail-party" source separation in a deep learning framework called deep clustering. Previous deep network approaches to separation have shown promising performance in… (More)

Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks

Hakan Erdogan, John R. Hershey, Shinji Watanabe, Jonathan Le Roux
IEEE International Conference on Acoustics…
2015

Separation of speech embedded in non-stationary interference is a challenging problem that has recently seen dramatic improvements using deep network-based methods. Previous work has shown that… (More)

Single-Channel Multi-Speaker Separation using Deep Clustering

Yusuf Isik, Jonathan Le Roux, Zhuo Chen, Shinji Watanabe, John R. Hershey
INTERSPEECH
2016

Deep clustering is a recently introduced deep learning architecture that uses discriminatively trained embeddings as the basis for clustering. It was recently applied to spectrogram segmentation,… (More)

The second ‘chime’ speech separation and recognition challenge: Datasets, tasks and baselines

Emmanuel Vincent, Jon Barker, Shinji Watanabe, Jonathan Le Roux, Francesco Nesta, Marco Matassoni
IEEE International Conference on Acoustics…
2013

Distant-microphone automatic speech recognition (ASR) remains a challenging goal in everyday environments involving multiple background sources and reverberation. This paper is intended to be a… (More)

Joint CTC-attention based end-to-end speech recognition using multi-task learning

Suyoun Kim, Takaaki Hori, Shinji Watanabe
IEEE International Conference on Acoustics…
2017

Recently, there has been an increasing interest in end-to-end speech recognition that directly transcribes speech to text without any predefined alignments. One approach is the attention-based… (More)

An analysis of environment, microphone and data simulation mismatches in robust speech recognition

Emmanuel Vincent, Shinji Watanabe, Aditya Nugraha, Jon Barker, Ricard Marxer
Computer Speech & Language
2017

Speech enhancement and automatic speech recognition (ASR) are most often evaluated in matched (or multi-condition) settings where the acoustic conditions of the training data match (or cover) those… (More)

Discriminative NMF and its application to single-channel source separation

Felix Weninger, Jonathan Le Roux, John R. Hershey, Shinji Watanabe
INTERSPEECH
2014

The objective of single-channel source separation is to accurately recover source signals from mixtures. Non-negative matrix factorization (NMF) is a popular approach for this task, yet previous NMF… (More)

The second ‘CHiME’ speech separation and recognition challenge: An overview of challenge systems and outcomes

Emmanuel Vincent, Jon Barker, Shinji Watanabe, Jonathan Le Roux, Francesco Nesta, Marco Matassoni
IEEE Workshop on Automatic Speech Recognition and…
2013

Distant-microphone automatic speech recognition (ASR) remains a challenging goal in everyday environments involving multiple background sources and reverberation. This paper reports on the results of… (More)

Speech Enhancement with LSTM Recurrent Neural Networks and its Application to Noise-Robust ASR

Felix Weninger, Hakan Erdogan, +4 authors Björn W. Schuller
LVA/ICA
2015

We evaluate some recent developments in recurrent neural network (RNN) based speech enhancement in the light of noise-robust automatic speech recognition (ASR). The proposed framework is based on… (More)

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