Shuoyang Ding bio photo

Shuoyang Ding

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I'm a research scientist in Amazon AWS AI working to advance the state-of-the-art of machine translation systems, primarily the Amazon Translate system. I defended my doctoral dissertation at the Johns Hopkins University in April, 2022 and am currently finishing up some minor dissertation corrections for the final submission. My dissertation 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.





  • 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]


  • Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation
    Weiting Tan, Shuoyang Ding, Huda Khayrallah, Philipp Koehn, 2021 [pdf]

  • 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]