Junkun Chen
Principal Applied Scientist at Microsoft
Redmond, Washington, United States
Summary
👤
Senior🎓
Top SchoolJunkun Chen is a Principal Applied Scientist at Microsoft AI Platform with 11 years of experience advancing speech and language technologies, specializing in simultaneous speech/text translation powered by modern LLMs. He holds a PhD in Computer Science from Oregon State University and built foundational research experience through internships at Baidu USA and ByteDance working on speech-and-text pretraining and NLU/text generation. At Microsoft he progressed from Senior to Principal Applied Scientist, bridging research and production to deploy streaming ASR and translation capabilities. He contributes to open-source speech toolkits—helping refine data processing and TIMIT support in the PaddleSpeech project, a widely used toolkit recognized with a NAACL demo award. Based in Redmond, he combines deep academic training with practical engineering, often focusing on the messy but crucial data-processing pipelines that make advanced speech systems reliable in production.
11 years of coding experience
4 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Fudan UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Oregon State UniversityBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Central South University
Github Skills (11)
sh10
script10
speech-recognition10
speech-synthesis10
shell10
asr10
scripting10
data-processing10
python9
freetts7
gtts7
Programming languages (2)
Github contributions (5)
PaddlePaddle/PaddleSpeech
Jul 2021 - Feb 2022
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 reviews, 47 commits, 30 PRs in 7 months
Contributions summary:Junkun primarily contributed to the development and refinement of scripts related to the TIMIT dataset, including creating manifest files and normalizing phonetic transcriptions. They also made modifications to shell scripts for data preparation and the execution of specific tasks within the project. These changes suggest a focus on data processing and the integration of speech-related datasets.
voice-recognitionasrtranslationspeech-recognitionstreaming-tts
LittleChenCc/DeepSpeech
Jun 2021 - Apr 2022
A PaddlePaddle ASR toolkit.
Contributions:119 pushes, 1 branch in 10 months
paddlepaddleasr
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.