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- FunAudioLLM CosyVoice - GitHub
CosyVoice 2 0 has been released! Compared to version 1 0, the new version offers more accurate, more stable, faster, and better speech generation capabilities Crosslingual Mixlingual：Support zero-shot voice cloning for cross-lingual and code-switching scenarios
- [2412. 10117] CosyVoice 2: Scalable Streaming Speech Synthesis with . . .
Therefore, in this report, we present an improved streaming speech synthesis model, CosyVoice 2, which incorporates comprehensive and systematic optimizations Specifically, we introduce finite-scalar quantization to improve the codebook utilization of speech tokens
- CosyVoice2. 0
By training on a large-scale multilingual dataset, CosyVoice 2 achieves human-comparable synthesis quality with very low response latency and real-time factor
- CosyVoice: Multilingual Text-to-Speech with Advanced Streaming
Introducing CosyVoice2, the leading-edge multilingual voice generation model for text-to-speech synthesis Now supporting zero-shot voice cloning, multiple languages, and dialects Perfect for real-time applications What is CosyVoice2?
- CosyVoice | Multilingual TTS Model
CosyVoice 2 0 available now! Introducing CosyVoice, a state-of-the-art multilingual voice generation model for high-fidelity text-to-speech synthesis Experience seamless voice cloning and ultra-fast streaming, now supporting a variety of languages What is CosyVoice?
- CosyVoice: Multilingual TTS with Real-time Synthesis
CosyVoice2-0 5B is your ultimate solution for multilingual voice generation, supporting multiple languages and dialects with cutting-edge features like zero-shot voice cloning and low-latency streaming synthesis Experience high-quality, natural speech output like never before
- FunAudioLLM CosyVoice2-0. 5B - Hugging Face
We strongly recommend using CosyVoice2-0 5B model for better streaming performance First, add third_party Matcha-TTS to your PYTHONPATH export PYTHONPATH=third_party Matcha-TTS
- CosyVoice 2. 0 - 阿里开源的语音生成大模型 | AI工具集
CosyVoice 2 0 是阿里巴巴通义实验室推出的CosyVoice语音生成大模型升级版，模型用有限标量量化技术提高码本利用率，简化文本-语音语言模型架构，推出块感知因果流匹配模型支持多样的合成场景。 CosyVoice 2 在发音准确性、音色一致性、韵律和音质上都有显著提升，MOS评测分从5 4提升到5 53，支持流式推理，大幅降低首包合成延迟至150ms，适合实时语音合成场景。 超低延迟的流式语音合成：支持双向流式语音合成，首包合成延迟可达150ms，适合实时应用场景。 高准确度的发音：相比前版本，发音错误率显著下降，尤其在处理绕口令、多音字、生僻字上表现突出。 音色一致性：在零样本和跨语言语音合成中保持音色高度一致性，提升合成自然度。
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