Hui Wang

Modeling fine-grained speaking styles remains challenging for language-speech representation pre-training, as existing speech-text models are typically trained with coarse captions or task-specific supervision, and scalable fine-grained style annotations are unavailable. We present FCaps, a large...

Generative speech technologies are progressing rapidly, but evaluating the perceptual quality of synthetic speech remains a core challenge. Existing methods typically rely on scalar scores or binary decisions, which lack interpretability and generalization across tasks and languages. We present S...

Automatic speech recognition (ASR) for children remains challenging due to developmental variability and the scarcity of high-quality corpora, especially for Mandarin and its dialects. In this paper, we present ChildTalk, a large-scale Chinese child speech corpus designed to address this gap. It...

Speech signals convey abundant speaker-related metadata, yet current privacy research predominantly focuses on identity-centric voiceprint protection, leaving sensitive Speaker Attribute Privacy (SAP) largely underexplored. This paper introduces AudioPrivacy, a large-scale Chinese dataset designe...

The advancement of Multimodal Emotion Recognition (MER) in Chinese is significantly hindered by the scarcity of high-quality, spontaneous dialogue datasets compared to their English counterparts. In this work, we introduce EmotionTalk, the first interactive Chinese multimodal dataset designed to...