DisCo_Speech: Controllable Zero-Shot Speech Generation with A Disentangled Speech Codec
Tao Li, Wenshuo Ge, Zhichao Wang, Zihao Cui, Yong Ma, Yingying Gao, Chao Deng, Shilei Zhang, Junlan Feng
摘要
Codec-based language models (LMs) have revolutionized text-to-speech (TTS). However, standard codecs entangle timbre and prosody, which hinders independent control in continuation-based LMs. To tackle this challenge, we propose DisCo-Speech, a zeroshot controllable TTS framework featuring a disentangled speech codec (DisCodec) and an LM-based generator. The core component Dis-Codec employs a two-stage design: 1) tri-factor disentanglement to separate speech into content, prosody, and timbre subspaces via parallel encoders and hybrid losses; and 2) fusion and reconstruction that merges content and prosody into unified content-prosody tokens suitable for LM prediction, while jointly optimizing reconstruction to address the disentanglementreconstruction trade-off. This allows the LM to perform prosodic continuation from a style prompt while the decoder injects target timbre, enabling flexible zero-shot control. Experiments demonstrate that DisCo-Speech achieves competitive voice cloning and superior zero-shot prosody control. By resolving the core entanglement at the codec level, DisCo-Speech provides a robust foundation for controllable speech synthesis. Audio samples are available at: https://disco-speech. github.io/DisCo-demo/ . Code and weights will be released at: https://github.com/ disco-speech/DisCo-Speech upon acceptance.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper12
- wav2vec 2.0: A Framework for Self-Supervised Learning of Speech RepresentationsAlexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, Michael AuliNeurIPS 2020 · 被引用 9,451 次
- Robust Speech Recognition via Large-Scale Weak SupervisionAlec Radford, Jong Wook Kim, Tao Xu, Greg Brockman 等ICML 2023 · 被引用 6,966 次
- HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech SynthesisJungil Kong, Jaehyeon Kim, Jaekyoung BaeNeurIPS 2020 · 被引用 2,890 次
- High-Fidelity Audio Compression with Improved RVQGANRithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar 等NeurIPS 2023 · 被引用 910 次
- Finite Scalar Quantization: VQ-VAE Made SimpleFabian Mentzer, David Minnen, Eirikur Agustsson, Michael TschannenICLR 2024 · 被引用 442 次
相关 Paper
- ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style ControlShengpeng Ji, Qian Chen, Wen Wang, Jialong Zuo 等ACL 2025
- NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion ModelsZeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan 等ICML 2024 · 被引用 341 次
- FC-TTS: Style and Timbre Control in Zero-Shot Text-to-Speech with Disentangled Speech RepresentationsYoonhyung Lee, Hyunsin Park, Jinhwan Park, Jinkyu LeeACL 2026
- Hierarchical Semantic-Acoustic Modeling via Semi-Discrete Residual Representations for Expressive End-to-End Speech SynthesisYixuan Zhou, Guoyang Zeng, Xin Liu, Xiang Li 等ICLR 2026
- MobileSpeech: A Fast and High-Fidelity Framework for Mobile Zero-Shot Text-to-SpeechShengpeng Ji, Ziyue Jiang, Hanting Wang, Jialong Zuo 等ACL 2024 · 被引用 1 次
