7 papers · 1 filter
TaigiSpeech: A Low-Resource Real-World Speech Intent Dataset and Preliminary Results with Scalable Data Mining In-the-Wild
Kai-Wei Chang, Yi-Cheng Lin, Huang-Cheng Chou +9
Speech technologies have advanced rapidly and serve diverse populations worldwide. However, many languages remain underrepresented due to limited resources. In this paper, we intro…
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…
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…
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…
How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models?
Mengqi Wang, Tiantian Feng, Shrikanth Narayanan
Large language models (LLMs) have enabled a wide variety of real-world applications in various domains. However, creating a high-performing application with high accuracy remains c…
Large Language Models based ASR Error Correction for Child Conversations
Anfeng Xu, Tiantian Feng, So Hyun Kim +3
Automatic Speech Recognition (ASR) has recently shown remarkable progress, but accurately transcribing children's speech remains a significant challenge. Recent developments in Lar…