12 papers
TF-MossFormer: Integrating Convolution Gated Local-Global Attentions for Enhanced Time-Frequency Domain Monaural Speech Separation
Shengkui Zhao, Zexu Pan, Haoxu Wang +3
Transformers with global attention capture long-range dependencies but can miss the fine-grained local continuity crucial for speech separation. We propose TF-MossFormer, a time-fr…
LuSeeL: Language-queried Binaural Universal Sound Event Extraction and Localization
Zexu Pan, Shengkui Zhao, Yukun Ma +4
Most universal sound extraction algorithms focus on isolating a target sound event from single-channel audio mixtures. However, the real world is three-dimensional, and binaural au…
Beyond Lips: Integrating Gesture and Lip Cues for Robust Audio-visual Speaker Extraction
Zexu Pan, Xinyuan Qian, Shengkui Zhao +2
Most audio-visual speaker extraction methods rely on synchronized lip recording to isolate the speech of a target speaker from a multi-talker mixture. However, in natural human com…
FlowSE-GRPO: Training Flow Matching Speech Enhancement via Online Reinforcement Learning
Haoxu Wang, Biao Tian, Yiheng Jiang +5
Generative speech enhancement offers a promising alternative to traditional discriminative methods by modeling the distribution of clean speech conditioned on noisy inputs. Post-tr…
Fun-ASR Technical Report
Keyu An, Yanni Chen, Zhigao Chen +35
In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling, model size scaling, and deep in…
ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment
Shengkui Zhao, Zexu Pan, Bin Ma
This paper introduces ClearerVoice-Studio, an open-source, AI-powered speech processing toolkit designed to bridge cutting-edge research and practical application. Unlike broad pla…
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…
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…
Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions
Kun Zhou, You Zhang, Dianwen Ng +3
Emotional text-to-speech (TTS) systems sturggle to capture the full spectrum of human emotions due to the inherent complexity of emotional expressions and the limited coverage of e…