Thanathai Lertpetchpun
tʰánátʰāj lɤ̂tpʰétpʰān
PhD Student in Electrical and Computer Engineering
University of Southern California
I research speech processing, focusing on speaker & emotion recognition, text to speech, voice conversion, accent conversion, and anti-spoofing. I am advised by Shrikanth Narayanan.
About Me
Hi, I am Thanathai and from Thailand (you can probably guess that from my first name). I am a second year PhD Student at the University of Southern California, where I'm a member of the Signal Analysis and Interpretation Laboratory (SAIL). My research interests are in speech processing. Specifically, I worked on speaker verification, voice anti-spoofing, and speech emotion recognition. Now I am working on text to speech model on how to control the accent strenght of non native speakers.
Before starting my PhD, I received my Bachelor's Degree in Computer Engineering from Chulalongkorn University, Thailand, where I also worked as a research assistant with Ekapol Chuangsuwanich on speaker verification and anti-spoofing. I've also had the opportunity to intern at Tencent Thailand in 2021, where I worked on news and song recommendation systems.
News
[Aug 2025] Three papers were accepted to Interspeech 2025!
[Aug 2023] One paper was accepted to Interspeech 2023!
Projects
ARTS: Anonymous Real-Time Speech
Oct 2024 - Present | USC - JHU - Meaning Company
- Proposed frameworks to develop state-of-the-art speech emotion recognition (SER) for predicting both emotional attributes and categorical emotions. They achieved 1st rank in emotional attributes and 2nd rank in categorical attributes in Naturalistic Conditions Challenge (2 Interspeech2025 publications)
- Developing zero-shot framework for multilingual TTS for accented English.
- Analalyzing the effect of speaker embedding on accent strength using phonemes rules to control the effect.
Speaker Recognition and Anti-spoofing System
Aug 2022 - May 2024 | Chulalongkorn University
- Proposed an approach to amplify artifacts in spoofed utterances using speech enhancement and show its robustness on different countermeasures and speech enhancement models (1 Interspeech2025 publication).
- Proposed a new normalization layer to address the problem of mismatched emotions and languages in speakerverification. (1 Interspeech2023 publication).
Awards & Honors
SER Challenge
Aug 2025
Rank 1st in attribute prediction and 2nd in category prediction on the Speech Emotion Recognition in Naturalistic Conditions Challenge.
Student Grant
Aug 2023
Awarded a Student Travel Grant for Interspeech 2023.