Biography
Hello! I am Haohan Guo (郭浩瀚), a PhD student @ CUHK, supervised by Prof. Helen Mei Ling MENG. Before it, I received my M.S. and B.S. degrees from Northwestern Polytechnical University, supervised by Prof. Lei Xie. Then, I worked as a researcher at Sogou Inc during 2020-2021. My current research topic is deep learning based speech synthesis. If you are interested in my works, welcome to contact me.
Interests
- Speech & Audio Processing
- Speech Synthesis
- Voice Conversion
- Audio Generation
Education
PhD in Computer Science, 2021-
The Chinese University of Hong Kong
MSc in Computer Science, 2017-2020
Northwestern Polytechnical University
BSc in Computer Science, 2013-2017
Northwestern Polytechnical University
Publications
Work Experience
lab, internship, full-time employee
Applied Scientist Intern
Work as an applied scientist intern to develop large-scale TTS system based on large language models (LLM).
Research Intern
Work as a researcher intern to investigate the application of speech representations in TTS.
Researcher
Work as a researcher on singing voice conversion. We aim to develop a commercial singing conversion system which can convert arbitrary singing voice to the target timbre. High sound quality and accurate melody expression are both required.
Research Intern
Research topic is multi-singer singing voice conversion. We propose a MelGAN based end-to-end PPG-SVC model. It significantly improves the sound quality and singer similarity over the conventional PPG-SVC framework. The work is summarized to the paper, Phonetic Posteriorgrams based Many-to-Many Singing Voice Conversion via Adversarial Training.
Research Intern
Supervised by Frank K. Soong and Lei He. We aim to improve the robustness and naturalness of end-to-end TTS. Two main works are published to INTERSPEECH 2019, A New GAN-based End-to-End TTS Training Algorithm and Exploiting Syntactic Features in a Parsed Tree to Improve End-to-End TTS. We also investigate the conversational TTS using the end-to-end approach. The work is published to SLT 2021, Conversational End-to-End TTS for Voice Agents.
Research Intern
Be responsible for the optimization of the front-end modules of TTS system, including G2P and Prosody model.
Education
Ph.D. Student
Supervised by Prof. Helen Meng.
M.S. Student
Supervised by Prof. Lei Xie.