5 papers
Laugh Now Cry Later: Controlling Time-Varying Emotional States of Flow-Matching-Based Zero-Shot Text-to-Speech
Haibin Wu, Xiaofei Wang, Sefik Emre Eskimez +8
People change their tones of voice, often accompanied by nonverbal vocalizations (NVs) such as laughter and cries, to convey rich emotions. However, most text-to-speech (TTS) syste…
E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS
Sefik Emre Eskimez, Xiaofei Wang, Manthan Thakker +10
This paper introduces Embarrassingly Easy Text-to-Speech (E2 TTS), a fully non-autoregressive zero-shot text-to-speech system that offers human-level naturalness and state-of-the-a…
Investigating Neural Audio Codecs for Speech Language Model-Based Speech Generation
Jiaqi Li, Dongmei Wang, Xiaofei Wang +13
Neural audio codec tokens serve as the fundamental building blocks for speech language model (SLM)-based speech generation. However, there is no systematic understanding on how the…
Exploring Robust Face-Voice Matching in Multilingual Environments
Jiehui Tang, Xiaofei Wang, Zhen Xiao +3
This paper presents Team Xaiofei's innovative approach to exploring Face-Voice Association in Multilingual Environments (FAME) at ACM Multimedia 2024. We focus on the impact of dif…
Total-Duration-Aware Duration Modeling for Text-to-Speech Systems
Sefik Emre Eskimez, Xiaofei Wang, Manthan Thakker +9
Accurate control of the total duration of generated speech by adjusting the speech rate is crucial for various text-to-speech (TTS) applications. However, the impact of adjusting t…