8 papers
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…
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…
Neurodyne: Neural Pitch Manipulation with Representation Learning and Cycle-Consistency GAN
Yicheng Gu, Chaoren Wang, Zhizheng Wu +1
Pitch manipulation is the process of producers adjusting the pitch of an audio segment to a specific key and intonation, which is essential in music production. Neural-network-base…
DualCodec: A Low-Frame-Rate, Semantically-Enhanced Neural Audio Codec for Speech Generation
Jiaqi Li, Xiaolong Lin, Zhekai Li +5
Neural audio codecs form the foundational building blocks for language model (LM)-based speech generation. Typically, there is a trade-off between frame rate and audio quality. Thi…