Hoyeon Lee

I am a Senior AI Research Scientist and Tech Lead in the Voice team at NAVER Cloud. My research focuses on Speech-Language & Multimodal AI and Large Language Models (LLMs), with the goal of building AI systems that understand, reason, and interact across speech, language, and context.

I develop language and speech technologies for real-world AI products, spanning pronunciation modeling, phrase break prediction, data generation, and model evaluation. Recently, I have been exploring how LLMs can extend these systems through multimodal reasoning, tool use, and scalable agentic applications. My work includes publications at EMNLP and INTERSPEECH.

I connect research and engineering through technical leadership, mentoring, and production deployment across NAVER’s services. Since April 2026, I have also served as an AI Technical Mentor at AI·SW Maestro, guiding two teams developing production-grade AI systems.

If you are interested in collaboration or would like to get in touch, please feel free to contact me.

news

Sep 2026	Our paper “Phonemizing User-Generated Text: A Benchmark, Taxonomy, and Compositional Approach” was accepted to EMNLP 2026.
Sep 2026	Excited to share that our work “LLM-Based Multi-Reference Evaluation for Efficient and Robust Assessment of Phrase Break Annotations” will appear at INTERSPEECH 2026. Looking forward to presenting it in Sydney, Australia 🇦🇺!
Apr 2026	I joined AI·SW Maestro as a Technical Mentor. Starting this year, I mentor two teams building production-grade AI systems across language modeling, speech AI, and multimodal intelligence.
Aug 2025	Our paper “Synthetic Data Generation for Phrase Break Prediction with Large Language Model” was accepted to INTERSPEECH 2025 in Rotterdam 🇳🇱.
Nov 2024	We presented our work “A Two-Step Approach for Data-Efficient French Pronunciation Learning” at EMNLP 2024 in Miami 🇺🇸.