Senior Applied Scientist at Microsoft
AI Cognitive Services
Microsoft Corporation, Redmond, WA, USA
E-mail: freewym AT gmail DOT com
Google Scholar
GitHub
| Biography |
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I am a Senior Applied Scientist in the Speech Research Group at Microsoft. I obtained my Ph.D. degree in Computer Science from Johns Hopkins University. At JHU, I was also affiliated with the Center for Language and Speech Processing (CLSP), advised by Prof. Sanjeev Khudanpur and former JHU Prof. Daniel Povey. I am mostly working on speech recognition (ASR) problems, and have broad interests in machine learning and natural language processing as well. I am one of the major contributors of the Kaldi project, and the owner of the open-source end-to-end ASR toolkit Espresso. I interned at Google’s speech team and Amazon’s Alexa ASR team in 2017 and 2018 respectively, working on end-to-end ASR.
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I received my B.S. and M.S. degree in Computer Science at Nanjing University in 2009 and 2012, respectively. My master advisor was Prof. Tong Lu.
| Education |
- Ph.D. in Computer Science
(Sep 2012 - Jul 2021)
Department of Computer Science
Johns Hopkins University, Baltimore, MD, USA
Advisors: Prof. Sanjeev Khudanpur and Dr. Daniel Povey
Thesis: Wake Word Detection and its Applications
- M.S. in Computer Science
(Sep 2009 - Jun 2012)
Department of Computer Science and Technology
Nanjing University, Nanjing, China
Advisor: Prof. Tong Lu
Thesis: Scene Image Understanding Based on Topic Modeling (in Chinese)
- B.S. in Computer Science
(Sep 2005 - Jun 2009)
Department of Computer Science and Technology
Nanjing University, Nanjing, China
| Work Experience |
- Senior Applied Scientist
AI Cognitive Services, Microsoft Corporation, Redmond, WA, USA (Sep 2020 - present)
Supervisor: Dr. Jinyu Li
- Applied Scientist Intern
Amazon.com, Inc., Seattle, WA, USA (May 2018 - Aug 2018)
I worked with Dr. Xing Fan, Dr. I-Fan Chen and Dr. Yuzong Liu on improving Seq2Seq ASR model with information extracted from anchored words for Amazon Alexa.
- Research Intern
Google LLC, Mountain View, CA, USA (May 2017 - Aug 2017)
I worked with Dr. Arun Narayanan, Dr. Rohit Prabhavalkar and Dr. Izhak Shafran on improving LAS model with time-frequency attention for robust ASR.
- Research Assistant
Center for Language and Speech Processing, Johns Hopkins University, MD, USA (Sep 2015 - Aug 2020)
I worked with Dr. Daniel Povey and Prof. Sanjeev Khudanpur on speech recognition, and contributed to the Kaldi project.
- Research Assistant
The Lieber Institute for Brain Development, Baltimore, MD, USA (Sep 2014 - Aug 2015)
I worked on multi-view learning for genomic and brain imaging data.
| Teaching Experience |
- Teaching Assistant
Johns Hopkins University (Fall 2016, Fall 2014, Spring 2014)
Course: Machine Learning
Instructor: Mark Dredze
- Teaching Assistant
Johns Hopkins University (Spring 2015)
Course: Information Retrieval and Web Agents
Instructor: David Yarowsky
- Teaching Assistant
Johns Hopkins University (Fall 2013)
Course: Machine Learning in Complex Domains
Instructor: Suchi Saria
- Teaching Assistant
Johns Hopkins University (Spring 2013)
Course: Algorithms for Sensor-based Robotics
Instructor: Gregory Hager
- Teaching Assistant
Nanjing University (Spring 2010)
Course: Programming in Java
Instructor: Ning Li
| Talks |
- Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
NVIDIA GPU Technology Conference (GTC) 2020
| Publications |
- LET-Decoder: A WFST-based Lazy-evaluation Token-group Decoder with Exact Lattice Generation
Hang Lv, Daniel Povey, Mahsa Yarmohammadi, Ke Li, Yiming Wang, Lei Xie, Sanjeev Khudanpur
IEEE Signal Processing Letters 2021 - Wake Word Detection with Streaming Transformers
Yiming Wang, Hang Lv, Daniel Povey, Lei Xie, Sanjeev Khudanpur
ICASSP 2021 - Wake Word Detection with Alignment-Free Lattice-Free MMI
Yiming Wang, Hang Lv, Daniel Povey, Lei Xie, Sanjeev Khudanpur
Interspeech 2020 - PyChain: A Fully Parallelized PyTorch Implementation of LF-MMI for End-to-End ASR
Yiwen Shao, Yiming Wang, Daniel Povey, Sanjeev Khudanpur
Interspeech 2020 - Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
Yiming Wang, Tongfei Chen, Hainan Xu, Shuoyang Ding, Hang Lv, Yiwen Shao, Nanyun Peng, Lei Xie, Shinji Watanabe, Sanjeev Khudanpur
ASRU 2019 - The JHU ASR System for VOiCES from a Distance Challenge 2019
Yiming Wang, David Snyder, Hainan Xu, Vimal Manohar, Phani Sankar Nidadavolu, Daniel Povey, Sanjeev Khudanpur
Interspeech 2019 - Robust Document Representations for Cross-Lingual Information Retrieval in Low-Resource Settings
Mahsa Yarmohammadi, Xutai Ma, Sorami Hisamoto, Muhammad Rahman, Yiming Wang, Hainan Xu, Daniel Povey, Philipp Koehn, Kevin Duh
Machine Translation Summit 2019 - End-to-end Anchored Speech Recognition
Yiming Wang, Xing Fan, I-Fan Chen, Yuzong Liu, Tongfei Chen, Björn Hoffmeister
ICASSP 2019 - A Pruned RNNLM Lattice-rescoring Algorithm for Automatic Speech Recognition
Hainan Xu, Tongfei Chen, Dongji Gao, Yiming Wang, Ke Li, Nagendra Goel, Yishay Carmiel, Daniel Povey, Sanjeev Khudanpur
ICASSP 2018 - Neural Network Language Modeling with Letter-based Features and Importance Sampling
Hainan Xu, Ke Li, Yiming Wang, Jian Wang, Shiyin Kang, Xie Chen, Daniel Povey, Sanjeev Khudanpur
ICASSP 2018 - Recurrent Neural Network Language Model Adaptation for Conversational Speech Recognition
Ke Li, Hainan Xu, Yiming Wang, Daniel Povey and Sanjeev Khudanpur
Interspeech 2018 - A GPU-based WFST Decoder with Exact Lattice Generation
Zhehuai Chen, Justin Luitjens, Hainan Xu, Yiming Wang, Daniel Povey, Sanjeev Khudanpur
Interspeech 2018 - Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks
Daniel Povey, Gaofeng Cheng, Yiming Wang, Ke Li, Hainan Xu, Mahsa Yarmohamadi, Sanjeev Khudanpur
Interspeech 2018 - Low Latency Acoustic Modeling Using Temporal Convolution and LSTMs
Vijayaditya Peddinti, Yiming Wang, Daniel Povey, Sanjeev Khudanpur
IEEE Signal Processing Letters 2018 - Backstitch: Counteracting Finite-sample Bias via Negative Steps
Yiming Wang, Vijayaditya Peddinti, Xiaohui Zhang, Daniel Povey, Sanjeev Khudanpur
Interspeech 2017 - The Kaldi OpenKWS System: Improving Low Resource Keyword Search
Jan Trmal, Matthew Wiesner, Vijayaditya Peddinti, Xiaohui Zhang, Pegah Ghahremani, Yiming Wang, Vimal Manohar, Hainan Xu, Daniel Povey, Sanjeev Khudanpur
Interspeech 2017 - Far-Field ASR Without Parallel Data
Vijayaditya Peddinti, Vimal Manohar, Yiming Wang, Daniel Povey, Sanjeev Khudanpur
Interspeech 2016 - Purely Sequence-Trained Neural Networks for ASR Based on Lattice-Free MMI
Daniel Povey, Vijayaditya Peddinti, Daniel Galvez, Pegah Ghahrmani, Vimal Manohar, Xingyu Na, Yiming Wang, Sanjeev Khudanpur
Interspeech 2016 - Weakly-supervised Region Annotation for Understanding Scene Images
Hao Wang, Tong Lu, Yiming Wang, Palaiahnakote Shivakumara, Chew Lim Tan
Multimedia Tools and Applications 2016 - Accelerated Mini-batch Randomized Block Coordinate Descent Method
Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu
NeurIPS 2014 - Learning Polylingual Topic Models from Code-Switched Social Media Documents
Nanyun Peng, Yiming Wang, Mark Dredze
ACL 2014 - 3D Model Comparison through Kernel Density Matching
Yiming Wang, Tong Lu, Rongjun Gao, Wenyin Liu
ICPR 2010 - QuickDiagram: A System for Online Sketching and Understanding of Diagrams
Wenyin Liu, Xiangfei Kong, Yiming Wang, Chester Wan, Cheuk-Yin Ho, Tong Lu, Zhengxing Sun
International Workshop on Graphics Recognition 2009