Shuoyang Ding bio photo

Shuoyang Ding

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I'm an applied scientist in Amazon AWS AI Labs working to advance the state-of-the-art of machine translation systems, primarily the Amazon Translate system. Prior to Amazon, I was a PhD student at Department of Computer Science, Johns Hopkins University. My PhD advisor was Philipp Koehn.

During my graduate studies, I was primarily affiliated with Center for Language and Speech Processing and also did research on neural machine translation. Yet, I was also invovled in several projects focused on broader problems of natural language processing (both text and speech). I had also spent a few memorable months either interning at Microsoft Translator, Salesforce Research, Amazon, or visiting The University of Edinburgh.

Before joining Johns Hopkins, I got my Bachelor's degree in Beijing University of Posts & Telecommunications. During the last year of my undergraduate study, I worked with Weiwei Sun in the Language Computing and Web Mining Group of Institute of Computer Science & Technology, Peking University, with a focus on semantic parsing and Chinese word segmentation.





  • Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation
    Weiting Tan, Shuoyang Ding, Huda Khayrallah, Philipp Koehn
    The 15th Conference of the Association for Machine Translation in the Americas (AMTA 2022) [pdf]

  • Runtime Audit of Neural Sequence Models for NLP
    Shuoyang Ding
    PhD Thesis [pdf]

  • The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task
    Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post, Christian Federmann, Philipp Koehn
    Sixth Conference on Machine Translation (WMT 2021) [pdf][poster]

  • Levenshtein Training for Word-level Quality Estimation
    Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post, Philipp Koehn
    EMNLP 2021 [pdf][code][slides][poster][talk]

  • Evaluating Saliency Methods for Neural Language Models
    Shuoyang Ding, Philipp Koehn
    NAACL 2021 [pdf][code][slides][talk]

  • 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 [pdf][code]

  • A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation
    Shuoyang Ding, Adithya Renduchintala, Kevin Duh
    MT Summit 2019 [pdf][code][poster]

  • An Exploration of Masking for Neural Machine Translation
    Matt Post, Shuoyang Ding, Marianna Martindale and Winston Wu
    MT Summit 2019 [pdf]

  • Saliency-driven Word Alignment Interpretation for Neural Machine Translation
    Shuoyang Ding, Hainan Xu, Philipp Koehn
    Fourth Conference on Machine Translation (WMT) 2019 [pdf][code][slides]

  • Parallelizable Stack Long Short-Term Memory
    Shuoyang Ding, Philipp Koehn
    NAACL 2019 Workshop on Structured Prediction for NLP [pdf][bib][code][slides]

  • Improving End-to-end Speech Recognition with Pronunciation-assisted Sub-word Modeling
    Hainan Xu, Shuoyang Ding, Shinji Watanabe
    ICASSP 2019 [pdf][bib][code]

  • Multi-Modal Data Augmentation for End-to-end ASR
    Adithya Renduchintala, Shuoyang Ding, Matthew Wiesner, Shinji Watanabe
    Interspeech 2018 Best Student Paper Award (3/700+) [pdf][bib]

  • The JHU Machine Translation Systems for WMT 2017
    Shuoyang Ding, Huda Khayrallah, Philipp Koehn, Matt Post, Gaurav Kumar, and Kevin Duh
    Second Conference on Machine Translation (WMT) 2017 [pdf][bib]

  • The JHU Machine Translation Systems for WMT 2016
    Shuoyang Ding, Kevin Duh, Huda Khayrallah, Philipp Koehn, and Matt Post
    First Conference on Machine Translation (WMT) 2016 [pdf][bib]

  • Grammatical Relations in Chinese: GB-Ground Extraction and Data-Driven Parsing
    Weiwei Sun, Yantao Du, Xin Kou, Shuoyang Ding, Xiaojun Wan
    Annual Meeting of the Association for Computational Linguistics (ACL) 2014 [pdf][bib]


  • How Do Source-side Monolingual Word Embeddings Impact Neural Machine Translation?
    Shuoyang Ding and Kevin Duh, 2018 [pdf]

  • Backstitch: Counteracting Finite-sample Bias via Negative Steps
    Yiming Wang, Hossein Hadian, Shuoyang Ding, Ke Li, Hainan Xu, Xiaohui Zhang, Daniel Povey, Sanjeev Khudanpur, 2017 [pdf]