Kyubyong Park
Chief Executive Officer at TUNiB
Gyeonggi, South Korea
Summary
🤩
Rockstar🎓
Top SchoolKyubyong Park is a computational linguist and CEO with nine years of hands-on experience applying deep learning to NLP and speech, now leading TUNiB after research leadership at Kakao Brain. He combines rigorous academic training (M.A. in Linguistics, SNU undergrad) with prolific open-source engineering—implementing TensorFlow versions of Transformer, Tacotron, DC-TTS, and practical G2P systems on his GitHub. His work spans end-to-end TTS, grapheme-to-phoneme conversion, multilingual word vectors, and lightweight speaker-adaptive voice cloning, reflecting a rare blend of lexicography expertise and production-ready ML engineering. He’s also an experienced language educator and author of more than ten Korean textbooks for learners, which informs his applied approach to linguistic problems. Based in Gyeonggi (Seoul), he runs open deep learning projects full-time and often ships reproducible research and training code that others can build on. Colleagues describe him as a practitioner-researcher who moves quickly from linguistic insight to deployable model.
9 years of coding experience
13 years of employment as a software developer
Bachelor's degree, Korean Language and Literature, Bachelor's degree, Korean Language and Literature at Seoul National UniversityMaster of Arts (M.A.), Linguistics, 3.97, Master of Arts (M.A.), Linguistics, 3.97 at University of Hawaii at Manoa
Korean, English, Japanese, Indonesian, Spanish, German, Chinese
Stackoverflow
1reputation
0reached
0answers
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Github Skills (23)
python10
architecture10
data-manipulation10
attention-mechanism10
machine-learning10
text-to-speech10
rnn-model10
speech-synthesis10
n10
numpy10
tensorflow10
speech10
neural-network10
transformer10
nlp10
Programming languages (4)
Github contributions (5)
Kyubyong/g2p
May 2018 - Dec 2019
g2p: English Grapheme To Phoneme Conversion
Role in this project:
ML Engineer
ML EngineerContributions:29 commits, 1 PR, 10 pushes in 1 year 8 months
Contributions summary:Kyubyong primarily contributed to building a Grapheme-to-Phoneme (G2P) conversion model using Python and TensorFlow. They modified and integrated existing code to create a system for converting English graphemes to phonemes, including incorporating homograph handling and number normalization functionalities. The user also defined and implemented a neural network model with attention mechanism for the G2P task, trained the model, and added features to predict pronunciations for out-of-vocabulary words.
g2pphoneme-conversionphonemepronunciationgrapheme-to-phoneme
Kyubyong/numpy_exercises
Nov 2016 - Feb 2019
Numpy exercises.
Role in this project:Data Scientist
Data ScientistContributions:38 commits, 7 PRs, 40 pushes in 2 years 2 months
Contributions summary:Kyubyong's commits primarily involve exercises focused on NumPy. The code changes include array creation, manipulation, and usage of mathematical and statistical functions. The contributions demonstrate the use of NumPy for data analysis and numerical computation, reflecting a data science focus within the repository's educational context. These changes enhance the understanding and application of core NumPy functionalities.
pythonnumpyscipynumpy-exercises
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