H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 55 Citations 12,286 277 World Ranking 2222 National Ranking 1190

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Speech recognition

Speech recognition, Artificial intelligence, Speech enhancement, Speech processing and Word error rate are his primary areas of study. His Speech recognition research incorporates themes from Artificial neural network and Recurrent neural network. Shinji Watanabe has included themes like Natural language processing and Pattern recognition in his Artificial intelligence study.

His Speech enhancement research is multidisciplinary, incorporating elements of Microphone array, Noise measurement and Speaker diarisation. When carried out as part of a general Speech processing research project, his work on Acoustic model is frequently linked to work in Open source, therefore connecting diverse disciplines of study. His Word error rate research is multidisciplinary, incorporating perspectives in Time delay neural network and Machine learning.

His most cited work include:

  • Deep clustering: Discriminative embeddings for segmentation and separation (691 citations)
  • The third ‘CHiME’ speech separation and recognition challenge: Dataset, task and baselines (429 citations)
  • Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks (402 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Speech recognition, Artificial intelligence, End-to-end principle, Pattern recognition and Artificial neural network. Shinji Watanabe has researched Speech recognition in several fields, including Speech enhancement, Decoding methods and Recurrent neural network. His Speech enhancement research includes themes of Microphone array and Source separation.

His research in Artificial intelligence intersects with topics in Machine learning and Natural language processing. The End-to-end principle study which covers Cluster analysis that intersects with Gibbs sampling. Noise is closely connected to Acoustic model in his research, which is encompassed under the umbrella topic of Pattern recognition.

He most often published in these fields:

  • Speech recognition (75.00%)
  • Artificial intelligence (39.50%)
  • End-to-end principle (24.16%)

What were the highlights of his more recent work (between 2019-2021)?

  • Speech recognition (75.00%)
  • End-to-end principle (24.16%)
  • Speaker diarisation (9.45%)

In recent papers he was focusing on the following fields of study:

Shinji Watanabe focuses on Speech recognition, End-to-end principle, Speaker diarisation, Transformer and Artificial intelligence. His work on Word error rate as part of general Speech recognition study is frequently connected to Autoregressive model, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His End-to-end principle study integrates concerns from other disciplines, such as Decoding methods, Connectionism and Near and far field.

The study incorporates disciplines such as Voice activity detection, Subtitle, Sequence and Cluster analysis in addition to Speaker diarisation. His Transformer research integrates issues from Self attention, Recurrent neural network, Computation and Reduction. The various areas that he examines in his Artificial intelligence study include Pattern recognition and Natural language processing.

Between 2019 and 2021, his most popular works were:

  • Espnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit (51 citations)
  • CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings (49 citations)
  • ESPnet-ST: All-in-One Speech Translation Toolkit (24 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Speech recognition

Speech recognition, End-to-end principle, Speaker diarisation, Transformer and Artificial intelligence are his primary areas of study. His Speech recognition study focuses on Source separation in particular. His study explores the link between End-to-end principle and topics such as Near and far field that cross with problems in Signal reconstruction and Transcription.

His research integrates issues of Artificial neural network, Subtitle, Track and Cluster analysis in his study of Speaker diarisation. In his study, Monotonic function and Computer engineering is strongly linked to Recurrent neural network, which falls under the umbrella field of Transformer. His Artificial intelligence study combines topics from a wide range of disciplines, such as Context, Pattern recognition and Natural language processing.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Deep clustering: Discriminative embeddings for segmentation and separation

John R. Hershey;Zhuo Chen;Jonathan Le Roux;Shinji Watanabe.
international conference on acoustics, speech, and signal processing (2016)

759 Citations

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

Jon Barker;Ricard Marxer;Emmanuel Vincent;Shinji Watanabe.
ieee automatic speech recognition and understanding workshop (2015)

518 Citations

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

Hakan Erdogan;John R. Hershey;Shinji Watanabe;Jonathan Le Roux.
international conference on acoustics, speech, and signal processing (2015)

468 Citations

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

Suyoun Kim;Takaaki Hori;Shinji Watanabe.
international conference on acoustics, speech, and signal processing (2017)

423 Citations

ESPNet: End-to-end speech processing toolkit

Shinji Watanabe;Takaaki Hori;Shigeki Karita;Tomoki Hayashi.
conference of the international speech communication association (2018)

374 Citations

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

Felix Weninger;Hakan Erdogan;Shinji Watanabe;Emmanuel Vincent.
international conference on latent variable analysis and signal separation (2015)

333 Citations

Hybrid CTC/Attention Architecture for End-to-End Speech Recognition

Shinji Watanabe;Takaaki Hori;Suyoun Kim;John R. Hershey.
IEEE Journal of Selected Topics in Signal Processing (2017)

287 Citations

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

Emmanuel Vincent;Jon Barker;Shinji Watanabe;Jonathan Le Roux.
international conference on acoustics, speech, and signal processing (2013)

273 Citations

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

Emmanuel Vincent;Shinji Watanabe;Aditya Arie Nugraha;Jon Barker.
Computer Speech & Language (2017)

269 Citations

A Comparative Study on Transformer vs RNN in Speech Applications

Shigeki Karita;Xiaofei Wang;Shinji Watanabe;Takenori Yoshimura.
2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) (2019)

218 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Shinji Watanabe

Tomohiro Nakatani

Tomohiro Nakatani

NTT (Japan)

Publications: 119

Keisuke Kinoshita

Keisuke Kinoshita

NTT (Japan)

Publications: 80

Jinyu Li

Jinyu Li

Microsoft (United States)

Publications: 71

Yu Tsao

Yu Tsao

Center for Information Technology

Publications: 69

Dong Yu

Dong Yu

Tencent (China)

Publications: 67

Takuya Yoshioka

Takuya Yoshioka

Microsoft (United States)

Publications: 65

Yifan Gong

Yifan Gong

Microsoft (United States)

Publications: 63

DeLiang Wang

DeLiang Wang

The Ohio State University

Publications: 61

Emmanuel Vincent

Emmanuel Vincent

University of Lorraine

Publications: 55

Reinhold Haeb-Umbach

Reinhold Haeb-Umbach

University of Paderborn

Publications: 54

Shoko Araki

Shoko Araki

NTT (Japan)

Publications: 50

Haizhou Li

Haizhou Li

Chinese University of Hong Kong, Shenzhen

Publications: 47

Jonathan Le Roux

Jonathan Le Roux

Mitsubishi Electric (United States)

Publications: 46

Jun Du

Jun Du

University of Science and Technology of China

Publications: 44

Tuomas Virtanen

Tuomas Virtanen

Tampere University

Publications: 41

Tara N. Sainath

Tara N. Sainath

Google (United States)

Publications: 38

Something went wrong. Please try again later.