1 citations · 3 across the 21 of their papers we have counts for
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Cross-modal Consistency Guidance for Robust Emotion Control in Auto-Regressive TTS Models
Yizhou Peng, Yukun Ma, Chong Zhang +4
While Text-to-Speech (TTS) systems enable emotional control via natural-language instructions, expressiveness, naturalness, and speech quality degrade when the target emotion confl…
FD-Bench: A Full-Duplex Benchmarking Pipeline Designed for Full Duplex Spoken Dialogue Systems
Yizhou Peng, Yi-Wen Chao, Dianwen Ng +4
Full-duplex spoken dialogue systems (FDSDS) enable more natural human-machine interactions by allowing real-time user interruptions and backchanneling, compared to traditional SDS…
Online Audio-Visual Autoregressive Speaker Extraction
Zexu Pan, Wupeng Wang, Shengkui Zhao +4
This paper proposes a novel online audio-visual speaker extraction model. In the streaming regime, most studies optimize the audio network only, leaving the visual frontend less ex…
DrVoice: Parallel Speech-Text Voice Conversation Model via Dual-Resolution Speech Representations
Chao-Hong Tan, Qian Chen, Wen Wang +14
Recent studies on end-to-end (E2E) speech generation with large language models (LLMs) have attracted significant community attention, with multiple works extending text-based LLMs…
Plug-and-Play Co-Occurring Face Attention for Robust Audio-Visual Speaker Extraction
Zexu Pan, Shengkui Zhao, Tingting Wang +4
Audio-visual speaker extraction isolates a target speaker's speech from a mixture speech signal conditioned on a visual cue, typically using the target speaker's face recording. Ho…
InspireMusic: Integrating Super Resolution and Large Language Model for High-Fidelity Long-Form Music Generation
Chong Zhang, Yukun Ma, Qian Chen +12
We introduce InspireMusic, a framework integrated super resolution and large language model for high-fidelity long-form music generation. A unified framework generates high-fidelit…
Conditional Latent Diffusion-Based Speech Enhancement Via Dual Context Learning
Shengkui Zhao, Zexu Pan, Kun Zhou +3
Recently, the application of diffusion probabilistic models has advanced speech enhancement through generative approaches. However, existing diffusion-based methods have focused on…
HiFi-SR: A Unified Generative Transformer-Convolutional Adversarial Network for High-Fidelity Speech Super-Resolution
Shengkui Zhao, Kun Zhou, Zexu Pan +3
The application of generative adversarial networks (GANs) has recently advanced speech super-resolution (SR) based on intermediate representations like mel-spectrograms. However, e…