Mu Yang

Mu Yang

About Me

Hi, there! My name is Mu Yang. I’m a 2nd year Ph.D. student in Electrical and Computer Engineering (ECE) at University of Texas at Dallas. My advisor is Dr. John H. L. Hansen. I’m a member of UTD Center for Robust Speech Systems (UTD CRSS).

My research interests include Speech Recognition and Speech Synthesis. My recent works have focused on accented (non-native) speech assessment and multilingual Automatic Speech Recognition. In the past, I also had experience in Spoken Language Understanding (Intent Classification) and Natural Language Processing (Event and Event Temporal Relation Extraction).

Interests
  • Speech Recognition
  • Speech Synthesis
  • Natural/Spoken Language Processing
Education

  • Ph.D. in Electrical and Computer Engineering, 2021-

    University of Texas at Dallas, USA

  • Ph.D. in Computer Science, 2020-2021 (quitted)

    Texas A&M University, USA

  • M.S. in Electrical Engineering, 2017-2019

    University of Southern California, USA

  • B.Eng. in Communication Engineering, 2013-2017

    Chongqing University, China

  • Exchange Student, 2016

    National Sun Yat-sen University, Taiwan

Publications

Mu Yang, Ram C. M. C. Shekar, Okim Kang,, John H. L. Hansen (2023). What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model. Interspeech 2023.

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Mu Yang, Andros Tjandra, Chunxi Liu, David Zhang, Duc Le, Ozlem Kalinli (2023). Learning ASR Pathways: A Sparse Multilingual ASR Model. ICASSP 2023.

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Mu Yang, Kevin Hirschi, Stephen D. Looney, Okim Kang,, John H. L. Hansen (2022). Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment. Interspeech 2022 (Oral).

PDF Audio Samples

Mu Yang, Shaojin Ding, Tianlong Chen, Tong Wang, Zhangyang Wang (2022). Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis. ICASSP 2022.

PDF Code Audio Samples

Mu Yang, Darpit Dave, Madhav Erraguntla, Gerard L. Cote, Ricardo Gutierrez-Osuna (2022). Joint Hypoglycemia Prediction and Glucose Forecasting via Deep Multi-task Learning. ICASSP 2022.

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Mingyu Derek Ma, Jiao Sun, Mu Yang, Kung-Hsiang Huang, Nuan Wen, Shikhar Singh, Rujun Han, Nanyun Peng (2021). EventPlus: A Temporal Event Understanding Pipeline. NAACL 2021 (Demonstrations).

PDF Code Demo

Mu Yang, Karolina Nurzynska, Ann E. Walts, Arkadiusz Gertych (2020). A CNN-based Active Learning Framework to Identify Mycobacteria in Digitized Ziehl-Neelsen Stained Human Tissues. Computerized Medical Imaging and Graphics 2020.

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Kung-Hsiang Huang, Mu Yang, Nanyun Peng (2020). Biomedical Event Extraction with Hierarchical Knowledge Graphs. EMNLP 2020 (Findings).

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Rujun Han, I-Hung Hsu, Mu Yang, Aram Galstyan, Ralph Weischedel, Nanyun Peng (2019). Deep Structured Neural Network for Event Temporal Relation Extraction. CoNLL 2019.

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Prashanth G. Shivakumar, Mu Yang, Panayiotis Georgiou (2019). Spoken Language Intent Detection using Confusion2Vec. InterSpeech 2019.

PDF Dataset

Experience

 
 
 
 
 
Microsoft
Research Intern
Microsoft
May 2023 – Aug 2023 Redmond, WA, USA

Mentors: Naoyuki Kanda, Xiaofei Wang. Manager: Takuya Yoshioka (Cognitive Services Research Speech team).

Speech Translation.

 
 
 
 
 
Meta AI
Research Intern
Meta AI
May 2022 – Aug 2022 New York City, NY, USA

Mentors: Andros Tjandra, Chunxi Liu, David Zhang. Manager: Duc Le, Ozlem Kalinli (AI Speech team).

Develop multilingual ASR technologies for on-device scenario.

 
 
 
 
 
USC ISI
Research Assistant
USC ISI
Jul 2019 – Jul 2020 Los Angeles, CA, USA

Supervisor: Nanyun Peng.

NLP projects (Information Extraction).

Selected Projects

Mu Yang
July, 2021 Project
Mis-pronunciation Detection based on Phoneme Recognition
Mis-pronunciation Detection based on Phoneme Recognition

A Mis-pronunciation Detection system, with word-level aligned phonemes predictions.
Audio Samples
Mu Yang, James Bunning, Shiyu Mou, Sharada Murali, Yixin Yang
December, 2018 USC course EE599: Deep Learning Lab for Speech Processing
Synthing: A WaveNet-based Singing Voice Synthisizer
Synthing: A WaveNet-based Singing Voice Synthisizer

Final project for USC course EE599: Deep Learning Lab for Speech Processing - a WaveNet-based singing voice synthesizer. This is a partial implementation of the paper A Neural Parametric Singing Synthesizer Modeling Timbre and Expression from Natural Songs.

PDF Code Dataset Audio Samples
Mu Yang, Tao Chen, Chang Su, Zhe Yang
November, 2018 USC course CSCI544: Applied Natural Language Processing
Collection and Classification of Lyrics
Collection and Classification of Lyrics

Web crawler of lyrics and corresponding music genre. Multiple baseline classifiers, such as Naive Bayes, SVM and Neural Approach(LSTM) are applied to identify the genre of a song by analyzing its lyrics.
PDF Code
Mu Yang
April, 2018 USC course EE522: Immersive Audio Processing
Digital Room Correction using Parallel Second-order Filter-based Equalizer
Digital Room Correction using Parallel Second-order Filter-based Equalizer

A Parallel second-order-based equalizer for Room Impulse Response Calibration.
PDF Code Audio Samples

Misc.

I love music! I play guitar (a lot), bass (a little), drum (a little) and violin (>10 years back). I play and sing in a few (unprofessional) bands. We covered songs from our favorite artists. Check out some of our videos!