no code implementations • 9 Apr 2021 • Rodrigo Cabrera, Xiaofeng Liu, Mohammadreza Ghodsi, Zebulun Matteson, Eugene Weinstein, Anjuli Kannan
Streaming processing of speech audio is required for many contemporary practical speech recognition tasks.
no code implementations • 20 Apr 2020 • Arindrima Datta, Bhuvana Ramabhadran, Jesse Emond, Anjuli Kannan, Brian Roark
Multilingual Automated Speech Recognition (ASR) systems allow for the joint training of data-rich and data-scarce languages in a single model.
no code implementations • 28 Mar 2020 • Tara N. Sainath, Yanzhang He, Bo Li, Arun Narayanan, Ruoming Pang, Antoine Bruguier, Shuo-Yiin Chang, Wei Li, Raziel Alvarez, Zhifeng Chen, Chung-Cheng Chiu, David Garcia, Alex Gruenstein, Ke Hu, Minho Jin, Anjuli Kannan, Qiao Liang, Ian McGraw, Cal Peyser, Rohit Prabhavalkar, Golan Pundak, David Rybach, Yuan Shangguan, Yash Sheth, Trevor Strohman, Mirko Visontai, Yonghui Wu, Yu Zhang, Ding Zhao
Thus far, end-to-end (E2E) models have not been shown to outperform state-of-the-art conventional models with respect to both quality, i. e., word error rate (WER), and latency, i. e., the time the hypothesis is finalized after the user stops speaking.
no code implementations • 6 Nov 2019 • Chung-Cheng Chiu, Wei Han, Yu Zhang, Ruoming Pang, Sergey Kishchenko, Patrick Nguyen, Arun Narayanan, Hank Liao, Shuyuan Zhang, Anjuli Kannan, Rohit Prabhavalkar, Zhifeng Chen, Tara Sainath, Yonghui Wu
In this paper, we both investigate and improve the performance of end-to-end models on long-form transcription.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 11 Sep 2019 • Anjuli Kannan, Arindrima Datta, Tara N. Sainath, Eugene Weinstein, Bhuvana Ramabhadran, Yonghui Wu, Ankur Bapna, Zhifeng Chen, Seungji Lee
Multilingual end-to-end (E2E) models have shown great promise in expansion of automatic speech recognition (ASR) coverage of the world's languages.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • ACL 2019 • Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yu-Hui Chen, Izhak Shafran
This paper describes novel models tailored for a new application, that of extracting the symptoms mentioned in clinical conversations along with their status.
2 code implementations • 21 Feb 2019 • Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia X. Chen, Ye Jia, Anjuli Kannan, Tara Sainath, Yuan Cao, Chung-Cheng Chiu, Yanzhang He, Jan Chorowski, Smit Hinsu, Stella Laurenzo, James Qin, Orhan Firat, Wolfgang Macherey, Suyog Gupta, Ankur Bapna, Shuyuan Zhang, Ruoming Pang, Ron J. Weiss, Rohit Prabhavalkar, Qiao Liang, Benoit Jacob, Bowen Liang, HyoukJoong Lee, Ciprian Chelba, Sébastien Jean, Bo Li, Melvin Johnson, Rohan Anil, Rajat Tibrewal, Xiaobing Liu, Akiko Eriguchi, Navdeep Jaitly, Naveen Ari, Colin Cherry, Parisa Haghani, Otavio Good, Youlong Cheng, Raziel Alvarez, Isaac Caswell, Wei-Ning Hsu, Zongheng Yang, Kuan-Chieh Wang, Ekaterina Gonina, Katrin Tomanek, Ben Vanik, Zelin Wu, Llion Jones, Mike Schuster, Yanping Huang, Dehao Chen, Kazuki Irie, George Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel A. U. Bacchiani, Thomas B. Jablin, Rob Suderman, Ian Williams, Benjamin Lee, Deepti Bhatia, Justin Carlson, Semih Yavuz, Yu Zhang, Ian McGraw, Max Galkin, Qi Ge, Golan Pundak, Chad Whipkey, Todd Wang, Uri Alon, Dmitry Lepikhin, Ye Tian, Sara Sabour, William Chan, Shubham Toshniwal, Baohua Liao, Michael Nirschl, Pat Rondon
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models.
3 code implementations • 5 Feb 2019 • Kazuki Irie, Rohit Prabhavalkar, Anjuli Kannan, Antoine Bruguier, David Rybach, Patrick Nguyen
We also investigate model complementarity: we find that we can improve WERs by up to 9% relative by rescoring N-best lists generated from a strong word-piece based baseline with either the phoneme or the grapheme model.
Ranked #42 on Speech Recognition on LibriSpeech test-clean
Language Modelling Sequence-To-Sequence Speech Recognition +1
2 code implementations • 15 Nov 2018 • Yanzhang He, Tara N. Sainath, Rohit Prabhavalkar, Ian McGraw, Raziel Alvarez, Ding Zhao, David Rybach, Anjuli Kannan, Yonghui Wu, Ruoming Pang, Qiao Liang, Deepti Bhatia, Yuan Shangguan, Bo Li, Golan Pundak, Khe Chai Sim, Tom Bagby, Shuo-Yiin Chang, Kanishka Rao, Alexander Gruenstein
End-to-end (E2E) models, which directly predict output character sequences given input speech, are good candidates for on-device speech recognition.
no code implementations • 7 Aug 2018 • Golan Pundak, Tara N. Sainath, Rohit Prabhavalkar, Anjuli Kannan, Ding Zhao
Our approach, which we re- fer to as Contextual Listen, Attend and Spell (CLAS) jointly- optimizes the ASR components along with embeddings of the context n-grams.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 27 Jul 2018 • Shubham Toshniwal, Anjuli Kannan, Chung-Cheng Chiu, Yonghui Wu, Tara N. Sainath, Karen Livescu
In this paper, we compare a suite of past methods and some of our own proposed methods for using unpaired text data to improve encoder-decoder models.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 6 Dec 2017 • Anjuli Kannan, Yonghui Wu, Patrick Nguyen, Tara N. Sainath, Zhifeng Chen, Rohit Prabhavalkar
Attention-based sequence-to-sequence models for automatic speech recognition jointly train an acoustic model, language model, and alignment mechanism.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 5 Dec 2017 • Tara N. Sainath, Rohit Prabhavalkar, Shankar Kumar, Seungji Lee, Anjuli Kannan, David Rybach, Vlad Schogol, Patrick Nguyen, Bo Li, Yonghui Wu, Zhifeng Chen, Chung-Cheng Chiu
However, there has been little previous work comparing phoneme-based versus grapheme-based sub-word units in the end-to-end modeling framework, to determine whether the gains from such approaches are primarily due to the new probabilistic model, or from the joint learning of the various components with grapheme-based units.
no code implementations • 5 Dec 2017 • Tara N. Sainath, Chung-Cheng Chiu, Rohit Prabhavalkar, Anjuli Kannan, Yonghui Wu, Patrick Nguyen, Zhifeng Chen
Neural transducer is a streaming sequence-to-sequence model, but has shown a significant degradation in performance compared to non-streaming models such as Listen, Attend and Spell (LAS).
2 code implementations • 5 Dec 2017 • Rohit Prabhavalkar, Tara N. Sainath, Yonghui Wu, Patrick Nguyen, Zhifeng Chen, Chung-Cheng Chiu, Anjuli Kannan
Sequence-to-sequence models, such as attention-based models in automatic speech recognition (ASR), are typically trained to optimize the cross-entropy criterion which corresponds to improving the log-likelihood of the data.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
4 code implementations • 5 Dec 2017 • 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
Attention-based encoder-decoder architectures such as Listen, Attend, and Spell (LAS), subsume the acoustic, pronunciation and language model components of a traditional automatic speech recognition (ASR) system into a single neural network.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 20 Nov 2017 • Chung-Cheng Chiu, Anshuman Tripathi, Katherine Chou, Chris Co, Navdeep Jaitly, Diana Jaunzeikare, Anjuli Kannan, Patrick Nguyen, Hasim Sak, Ananth Sankar, Justin Tansuwan, Nathan Wan, Yonghui Wu, Xuedong Zhang
We explored both CTC and LAS systems for building speech recognition models.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 27 Jan 2017 • Anjuli Kannan, Oriol Vinyals
The recent application of RNN encoder-decoder models has resulted in substantial progress in fully data-driven dialogue systems, but evaluation remains a challenge.
no code implementations • 15 Jun 2016 • Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, Laszlo Lukacs, Marina Ganea, Peter Young, Vivek Ramavajjala
In this paper we propose and investigate a novel end-to-end method for automatically generating short email responses, called Smart Reply.