collaborators

10 papers

eess.AS2026

Trade-offs Between Capacity and Robustness in Neural Audio Codecs for Adversarially Robust Speech Recognition

Jordan Prescott, Thanathai Lertpetchpun, Shrikanth Narayanan

Adversarial perturbations exploit vulnerabilities in automatic speech recognition (ASR) systems while preserving human perceived linguistic content. Neural audio codecs impose a di…

cs.CL2026

Learning-free L2-Accented Speech Generation using Phonological Rules

Thanathai Lertpetchpun, Yoonjeong Lee, Jihwan Lee +3

Accent plays a crucial role in speaker identity and inclusivity in speech technologies. Existing accented text-to-speech (TTS) systems either require large-scale accented datasets…

cs.CL2026

Accent Vector: Controllable Accent Manipulation for Multilingual TTS Without Accented Data

Thanathai Lertpetchpun, Thanapat Trachu, Jihwan Lee +3

Accent is an integral part of society, reflecting multiculturalism and shaping how individuals express identity. The majority of English speakers are non-native (L2) speakers, yet…

cs.CL2026

Quantifying Speaker Embedding Phonological Rule Interactions in Accented Speech Synthesis

Thanathai Lertpetchpun, Yoonjeong Lee, Thanapat Trachu +4

Many spoken languages, including English, exhibit wide variation in dialects and accents, making accent control an important capability for flexible text-to-speech (TTS) models. Cu…

eess.AS2025

ARTI-6: Towards Six-dimensional Articulatory Speech Encoding

Jihwan Lee, Sean Foley, Thanathai Lertpetchpun +6

We propose ARTI-6, a compact six-dimensional articulatory speech encoding framework derived from real-time MRI data that captures crucial vocal tract regions including the velum, t…

cs.SD2025

Voxlect: A Speech Foundation Model Benchmark for Modeling Dialects and Regional Languages Around the Globe

Tiantian Feng, Kevin Huang, Anfeng Xu +6

We present Voxlect, a novel benchmark for modeling dialects and regional languages worldwide using speech foundation models. Specifically, we report comprehensive benchmark evaluat…