OpenSpeech's Contributors

It records developers and contributions that contributed to OpenSpeech.

Soohwan Kim

• Creator, Lead Development, Main Contributor

• Program architecture design

• Model implementation list:

  1. DeepSpeech2 (from Baidu Research) released with paper Deep Speech 2: End-to-End Speech Recognition in English and Mandarin, by Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu.
  2. RNN-Transducer (from University of Toronto) released with paper Sequence Transduction with Recurrent Neural Networks, by Alex Graves.
  3. LSTM Language Model (from RWTH Aachen University) released with paper LSTM Neural Networks for Language Modeling, by Martin Sundermeyer, Ralf Schluter, and Hermann Ney.
  4. Listen Attend Spell (from Carnegie Mellon University and Google Brain) released with paper Listen, Attend and Spell, by William Chan, Navdeep Jaitly, Quoc V. Le, Oriol Vinyals.
  5. Location-aware attention based Listen Attend Spell (from University of Wrocław and Jacobs University and Universite de Montreal) released with paper Attention-Based Models for Speech Recognition, by Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, Yoshua Bengio.
  6. Joint CTC-Attention based Listen Attend Spell (from Mitsubishi Electric Research Laboratories and Carnegie Mellon University) released with paper Joint CTC-Attention based End-to-End Speech Recognition using Multi-task Learning, by Suyoun Kim, Takaaki Hori, Shinji Watanabe.
  7. Deep CNN Encoder with Joint CTC-Attention Listen Attend Spell (from Mitsubishi Electric Research Laboratories and Massachusetts Institute of Technology and Carnegie Mellon University) released with paper Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LM, by Takaaki Hori, Shinji Watanabe, Yu Zhang, William Chan.
  8. Multi-head attention based Listen Attend Spell (from Google) released with paper State-of-the-art Speech Recognition With Sequence-to-Sequence Models, by Chung-Cheng Chiu, Tara N. Sainath, Yonghui Wu, Rohit Prabhavalkar, Patrick Nguyen, Zhifeng Chen, Anjuli Kannan, Ron J. Weiss, Kanishka Rao, Ekaterina Gonina, Navdeep Jaitly, Bo Li, Jan Chorowski, Michiel Bacchiani.
  9. Speech-Transformer (from University of Chinese Academy of Sciences and Institute of Automation and Chinese Academy of Sciences) released with paper Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition, by Linhao Dong; Shuang Xu; Bo Xu.
  10. VGG-Transformer (from Facebook AI Research) released with paper Transformers with convolutional context for ASR, by Abdelrahman Mohamed, Dmytro Okhonko, Luke Zettlemoyer.
  11. Transformer with CTC (from NTT Communication Science Laboratories, Waseda University, Center for Language and Speech Processing, Johns Hopkins University) released with paper Improving Transformer-based End-to-End Speech Recognition with Connectionist Temporal Classification and Language Model Integration, by Shigeki Karita, Nelson Enrique Yalta Soplin, Shinji Watanabe, Marc Delcroix, Atsunori Ogawa, Tomohiro Nakatani.
  12. Joint CTC-Attention based Transformer(from NTT Corporation) released with paper Self-Distillation for Improving CTC-Transformer-based ASR Systems, by Takafumi Moriya, Tsubasa Ochiai, Shigeki Karita, Hiroshi Sato, Tomohiro Tanaka, Takanori Ashihara, Ryo Masumura, Yusuke Shinohara, Marc Delcroix.
  13. Transformer Language Model (from Amazon Web Services) released with paper Language Models with Transformers, by Chenguang Wang, Mu Li, Alexander J. Smola.
  14. Jasper (from NVIDIA and New York University) released with paper Jasper: An End-to-End Convolutional Neural Acoustic Model, by Jason Li, Vitaly Lavrukhin, Boris Ginsburg, Ryan Leary, Oleksii Kuchaiev, Jonathan M. Cohen, Huyen Nguyen, Ravi Teja Gadde.
  15. QuartzNet (from NVIDIA and Univ. of Illinois and Univ. of Saint Petersburg) released with paper QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions, by Samuel Kriman, Stanislav Beliaev, Boris Ginsburg, Jocelyn Huang, Oleksii Kuchaiev, Vitaly Lavrukhin, Ryan Leary, Jason Li, Yang Zhang.
  16. Conformer (from Google) released with paper Conformer: Convolution-augmented Transformer for Speech Recognition, by Anmol Gulati, James Qin, Chung-Cheng Chiu, Niki Parmar, Yu Zhang, Jiahui Yu, Wei Han, Shibo Wang, Zhengdong Zhang, Yonghui Wu, Ruoming Pang.
  17. Conformer with CTC (from Northwestern Polytechnical University and University of Bordeaux and Johns Hopkins University and Human Dataware Lab and Kyoto University and NTT Corporation and Shanghai Jiao Tong University and Chinese Academy of Sciences) released with paper Recent Developments on ESPNET Toolkit Boosted by Conformer, by Pengcheng Guo, Florian Boyer, Xuankai Chang, Tomoki Hayashi, Yosuke Higuchi, Hirofumi Inaguma, Naoyuki Kamo, Chenda Li, Daniel Garcia-Romero, Jiatong Shi, Jing Shi, Shinji Watanabe, Kun Wei, Wangyou Zhang, Yuekai Zhang.
  18. Conformer with LSTM Decoder (from IBM Research AI) released with paper On the limit of English conversational speech recognition, by Zoltán Tüske, George Saon, Brian Kingsbury.

• Recipe:

  1. LibriSpeech
  2. AISHELL-1
  3. KsponSpeech

Sangchun Ha

• Maintainer, Main Contributor.

• Code validation

• Model implementation list:

  1. Transformer Transducer (from Facebook AI) released with paper Transformer-Transducer: End-to-End Speech Recognition with Self-Attention, by Ching-Feng Yeh, Jay Mahadeokar, Kaustubh Kalgaonkar, Yongqiang Wang, Duc Le, Mahaveer Jain, Kjell Schubert, Christian Fuegen, Michael L. Seltzer.
  2. ContextNet (from Google) released with paper ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context, by Wei Han, Zhengdong Zhang, Yu Zhang, Jiahui Yu, Chung-Cheng Chiu, James Qin, Anmol Gulati, Ruoming Pang, Yonghui Wu.
  3. Squeezeformer (from Berkeley) released with paper Squeezeformer: An Efficient Transformer for Automatic Speech Recognition, by Sehoon Kim, Amir Gholami, Albert Shaw, Nicholas Lee, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Kurt Keutzer.

• Beam search:

  1. RNN Transducer beam search
  2. Transformer Transducer beam search

Soyoung Cho

• Main Contributor.
• Usability Check
• Documentation
• Logo design

Younghun Kim

• Contributor.
• Optimizing the KsponSpeech preprocessing