2 citations · 2 across the 7 of their papers we have counts for
11 papers
A Unified Neural Codec Language Model for Selective Editable Text to Speech Generation
Hanchen Pei, Shujie Liu, Yanqing Liu +5
Neural codec language models achieve impressive zero-shot Text-to-Speech (TTS) by fully imitating the acoustic characteristics of a short speech prompt, including timbre, prosody,…
TrInk: Ink Generation with Transformer Network
Zezhong Jin, Shubhang Desai, Xu Chen +8
In this paper, we propose TrInk, a Transformer-based model for ink generation, which effectively captures global dependencies. To better facilitate the alignment between the input…
Next Tokens Denoising for Speech Synthesis
Yanqing Liu, Ruiqing Xue, Chong Zhang +7
While diffusion and autoregressive (AR) models have significantly advanced generative modeling, they each present distinct limitations. AR models, which rely on causal attention, c…
StreamMel: Real-Time Zero-shot Text-to-Speech via Interleaved Continuous Autoregressive Modeling
Hui Wang, Yifan Yang, Shujie Liu +7
Recent advances in zero-shot text-to-speech (TTS) synthesis have achieved high-quality speech generation for unseen speakers, but most systems remain unsuitable for real-time appli…
Zero-Shot Streaming Text to Speech Synthesis with Transducer and Auto-Regressive Modeling
Haiyang Sun, Shujie Hu, Shujie Liu +8
Zero-shot streaming text-to-speech is an important research topic in human-computer interaction. Existing methods primarily use a lookahead mechanism, relying on future text to ach…
MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning
Peng Xia, Jinglu Wang, Yibo Peng +10
Medical Large Vision-Language Models (Med-LVLMs) have shown strong potential in multimodal diagnostic tasks. However, existing single-agent models struggle to generalize across div…