Keon Lee is a deep learning researcher based in Seoul with 8 years of experience focused on conversational AI and generative models. Currently at KRAFTON's GenAI research division, he specializes in text-to-speech as part of a broader vision to build personality-rich agents that listen, think, and speak like humans. Previously a data scientist at LOVO AI, he brings hands-on industry experience in speech and voice technologies grounded in an MEng from KAIST. Practical yet research-minded, Keon combines industrial product exposure with academic rigor in computing and industrial design, enabling him to shape both the technical and experiential aspects of voice agents. His long-term goal—to create agents with distinctive, human-like personalities—drives his focused work on TTS as the most direct vehicle for expressing individuality in AI.
8 years of coding experience
1 year of employment as a software developer
Master of Engineering - MEng, School of Computing, Master of Engineering - MEng, School of Computing at 한국과학기술원(KAIST)
PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques to enforce the robustness and efficiency of the model.
Contributions:3 releases, 5 commits, 7 pushes in 7 months
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