6 papers · 1 filter
Evaluating the Expressive Appropriateness of Speech in Rich Contexts
Tianrui Wang, Ziyang Ma, Yizhou Peng +26
Evaluating expressive speech remains challenging, as existing methods mainly assess emotional intensity and overlook whether a speech sample is expressively appropriate for its con…
Efficient Emotion and Speaker Adaptation in LLM-Based TTS via Characteristic-Specific Partial Fine-Tuning
Tianrui Wang, Meng Ge, Cheng Gong +11
While LLM-based TTS models exhibit zero-shot emotion and speaker cloning, their cloning fidelity and pronunciation clarity degrade on unseen domains. Fine-tuning is essential for a…
Word-Level Emotional Expression Control in Zero-Shot Text-to-Speech Synthesis
Tianrui Wang, Haoyu Wang, Meng Ge +10
While emotional text-to-speech (TTS) has made significant progress, most existing research remains limited to utterance-level emotional expression and fails to support word-level c…
Learning Time-Graph Frequency Representation for Monaural Speech Enhancement
Tingting Wang, Tianrui Wang, Meng Ge +2
The Graph Fourier Transform (GFT) has recently demonstrated promising results in speech enhancement. However, existing GFT-based speech enhancement approaches often employ fixed gr…
LORT: Locally Refined Convolution and Taylor Transformer for Monaural Speech Enhancement
Junyu Wang, Zizhen Lin, Tianrui Wang +3
Achieving superior enhancement performance while maintaining a low parameter count and computational complexity remains a challenge in the field of speech enhancement. In this pape…
Time-Graph Frequency Representation with Singular Value Decomposition for Neural Speech Enhancement
Tingting Wang, Tianrui Wang, Meng Ge +3
Time-frequency (T-F) domain methods for monaural speech enhancement have benefited from the success of deep learning. Recently, focus has been put on designing two-stream network m…