What are Open Source Text-to-Speech Models?
Open source text-to-speech models are specialized AI systems that convert written text into natural-sounding human speech. Using advanced deep learning architectures and neural networks, they transform text input into high-quality audio output with realistic pronunciation, intonation, and emotional expression. This technology enables developers and creators to build voice-enabled applications, accessibility tools, and interactive experiences with unprecedented freedom. They foster collaboration, accelerate innovation, and democratize access to powerful speech synthesis tools, enabling a wide range of applications from voice assistants to large-scale enterprise communication solutions.
Fish Speech V1.5
Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model employing an innovative DualAR architecture with dual autoregressive transformer design. It supports multiple languages with over 300,000 hours of training data for English and Chinese, and over 100,000 hours for Japanese. In independent TTS Arena evaluations, it achieved an exceptional ELO score of 1339 with a word error rate of 3.5% and character error rate of 1.2% for English.
Fish Speech V1.5: Multilingual Excellence with DualAR Architecture
Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model employing an innovative DualAR architecture with dual autoregressive transformer design. It supports multiple languages with over 300,000 hours of training data for English and Chinese, and over 100,000 hours for Japanese. In independent TTS Arena evaluations, it achieved an exceptional ELO score of 1339 with a word error rate of 3.5% and character error rate of 1.2% for English, and 1.3% character error rate for Chinese characters.
Pros
- Innovative DualAR architecture with dual autoregressive transformers.
- Exceptional performance with ELO score of 1339 in TTS Arena.
- Extensive multilingual training data (300k+ hours).
Cons
- Higher pricing at $15/M UTF-8 bytes from SiliconFlow.
- May require technical expertise for optimal implementation.
Why We Love It
- It delivers industry-leading multilingual speech synthesis with proven benchmark performance and innovative DualAR architecture for superior quality.
CosyVoice2-0.5B
CosyVoice 2 is a streaming speech synthesis model based on a large language model with unified streaming/non-streaming framework design. It achieves ultra-low latency of 150ms in streaming mode while maintaining synthesis quality identical to non-streaming mode. Compared to version 1.0, pronunciation errors are reduced by 30-50%, MOS score improved from 5.4 to 5.53, with fine-grained control over emotions and dialects.
CosyVoice2-0.5B: Ultra-Low Latency Streaming TTS
CosyVoice 2 is a streaming speech synthesis model based on a large language model with unified streaming/non-streaming framework design. It enhances speech token codebook utilization through finite scalar quantization (FSQ) and develops a chunk-aware causal streaming matching model. In streaming mode, it achieves ultra-low latency of 150ms while maintaining synthesis quality identical to non-streaming mode. Compared to version 1.0, pronunciation errors are reduced by 30-50%, MOS score improved from 5.4 to 5.53. The model supports Chinese (including dialects: Cantonese, Sichuan, Shanghainese, Tianjin), English, Japanese, Korean, and cross-lingual scenarios.
Pros
- Ultra-low latency of 150ms in streaming mode.
- 30-50% reduction in pronunciation errors vs v1.0.
- Improved MOS score from 5.4 to 5.53.
Cons
- Smaller model size (0.5B parameters) may limit complexity.
- Streaming quality dependent on network conditions.
Why We Love It
- It revolutionizes real-time speech synthesis with 150ms latency while maintaining exceptional quality and supporting diverse languages and dialects.
IndexTTS-2
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech model designed for precise duration control in large-scale TTS systems. It supports two modes: explicit token specification for precise duration and free auto-regressive generation. The model achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts with enhanced speech clarity.
IndexTTS-2: Zero-Shot TTS with Precision Duration Control
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech model addressing precise duration control challenges in large-scale TTS systems, crucial for applications like video dubbing. It supports two modes: explicit token specification for precise duration and free auto-regressive generation. The model achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts. It incorporates GPT latent representations and utilizes a novel three-stage training paradigm for enhanced speech clarity. A soft instruction mechanism based on text descriptions, developed by fine-tuning Qwen3, guides emotional tone generation. Experimental results show IndexTTS2 outperforms state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity.
Pros
- Precise duration control for video dubbing applications.
- Independent control over timbre and emotional expression.
- Zero-shot capability with superior speaker similarity.
Cons
- Requires input pricing at $7.15/M UTF-8 bytes from SiliconFlow.
- Complex architecture may require advanced technical knowledge.
Why We Love It
- It pioneers precise duration control and emotional disentanglement in zero-shot TTS, making it perfect for professional video dubbing and expressive speech applications.
Text-to-Speech Model Comparison
In this table, we compare 2025's leading open source TTS models, each with unique strengths. For multilingual excellence, Fish Speech V1.5 provides industry-leading performance. For real-time applications, CosyVoice2-0.5B offers ultra-low latency streaming. For precise control, IndexTTS-2 delivers zero-shot capabilities with duration precision. This side-by-side view helps you choose the right tool for your specific speech synthesis needs.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | Fish Speech V1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | Multilingual excellence with DualAR |
| 2 | CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | Ultra-low latency streaming (150ms) |
| 3 | IndexTTS-2 | IndexTeam | Text-to-Speech | $7.15/M UTF-8 bytes | Zero-shot with duration control |
Frequently Asked Questions
Our top three picks for 2025 are Fish Speech V1.5, CosyVoice2-0.5B, and IndexTTS-2. Each of these models stood out for their innovation, performance, and unique approach to solving challenges in text-to-speech synthesis, multilingual support, and real-time generation.
Our in-depth analysis shows several leaders for different needs. Fish Speech V1.5 is the top choice for multilingual applications requiring highest quality with proven benchmark performance. CosyVoice2-0.5B excels in real-time streaming applications with 150ms latency. IndexTTS-2 is ideal for video dubbing and applications requiring precise duration control and emotional expression.