10 papers · 1 filter
MimicLM: Zero-Shot Voice Imitation through Autoregressive Modeling of Pseudo-Parallel Speech Corpora
Tao Feng, Yuxiang Wang, Yuancheng Wang +5
Voice imitation aims to transform source speech to match a reference speaker's timbre and speaking style while preserving linguistic content. A straightforward approach is to train…
SpeechJudge: Towards Human-Level Judgment for Speech Naturalness
Xueyao Zhang, Chaoren Wang, Huan Liao +8
Aligning large generative models with human feedback is a critical challenge. In speech synthesis, this is particularly pronounced due to the lack of a large-scale human preference…
SP-MCQA: Evaluating Intelligibility of TTS Beyond the Word Level
Hitomi Jin Ling Tee, Chaoren Wang, Zijie Zhang +1
The evaluation of intelligibility for TTS has reached a bottleneck, as existing assessments heavily rely on word-by-word accuracy metrics such as WER, which fail to capture the com…
Vevo2: A Unified and Controllable Framework for Speech and Singing Voice Generation
Xueyao Zhang, Junan Zhang, Yuancheng Wang +5
Controllable human voice generation, particularly for expressive domains like singing, remains a significant challenge. This paper introduces Vevo2, a unified framework for control…
Advancing Zero-shot Text-to-Speech Intelligibility across Diverse Domains via Preference Alignment
Xueyao Zhang, Yuancheng Wang, Chaoren Wang +3
Modern zero-shot text-to-speech (TTS) systems, despite using extensive pre-training, often struggle in challenging scenarios such as tongue twisters, repeated words, code-switching…
SingNet: Towards a Large-Scale, Diverse, and In-the-Wild Singing Voice Dataset
Yicheng Gu, Chaoren Wang, Junan Zhang +4
The lack of a publicly-available large-scale and diverse dataset has long been a significant bottleneck for singing voice applications like Singing Voice Synthesis (SVS) and Singin…