What are Open Source Text-to-Audio Narration Models?
Open source text-to-audio narration models are specialized AI systems that convert written text into natural-sounding speech. Using advanced deep learning architectures like autoregressive transformers and neural vocoders, they translate text descriptions into high-quality audio narration. This technology allows developers and creators to generate speech content with unprecedented flexibility and control. They foster collaboration, accelerate innovation, and democratize access to powerful voice synthesis tools, enabling a wide range of applications from audiobook production to multilingual content creation and enterprise voice 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 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% CER for Chinese.
Fish Speech V1.5: Industry-Leading Multilingual Narration
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 evaluations by TTS Arena, the model performed exceptionally well, with an ELO score of 1339. The model achieved a word error rate (WER) of 3.5% and a character error rate (CER) of 1.2% for English, and a CER of 1.3% for Chinese characters.
Pros
- Industry-leading ELO score of 1339 in TTS Arena.
- Exceptional accuracy with 3.5% WER for English.
- Massive training data: 300k+ hours for English/Chinese.
Cons
- Higher pricing at $15/M UTF-8 bytes on SiliconFlow.
- Limited language support compared to some competitors.
Why We Love It
- It sets the gold standard for text-to-speech quality with proven arena performance and exceptional multilingual accuracy for professional narration applications.
CosyVoice2-0.5B
CosyVoice 2 is a streaming speech synthesis model based on large language model architecture, featuring unified streaming/non-streaming framework design. It achieves ultra-low latency of 150ms in streaming mode while maintaining high synthesis quality. Compared to v1.0, pronunciation errors reduced by 30-50%, MOS score improved from 5.4 to 5.53, supporting Chinese dialects, English, Japanese, Korean with cross-lingual capabilities.
CosyVoice2-0.5B: Ultra-Low Latency Streaming Excellence
CosyVoice 2 is a streaming speech synthesis model based on a large language model, employing a unified streaming/non-streaming framework design. The model enhances the utilization of the speech token codebook through finite scalar quantization (FSQ), simplifies the text-to-speech language model architecture, and develops a chunk-aware causal streaming matching model that supports different synthesis scenarios. In streaming mode, the model achieves ultra-low latency of 150ms while maintaining synthesis quality almost identical to that of non-streaming mode. Compared to version 1.0, the pronunciation error rate has been reduced by 30%-50%, the MOS score has improved from 5.4 to 5.53, and fine-grained control over emotions and dialects is supported.
Pros
- Ultra-low latency of 150ms in streaming mode.
- 30-50% reduction in pronunciation error rate vs v1.0.
- Improved MOS score from 5.4 to 5.53.
Cons
- Smaller 0.5B parameter size may limit voice quality.
- Primarily optimized for Asian languages.
Why We Love It
- It delivers real-time narration capabilities with exceptional latency performance, perfect for live applications and interactive voice experiences.
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 features disentangled emotional expression and speaker identity control, enabling independent timbre and emotion manipulation via separate prompts. The model incorporates GPT latent representations and a novel three-stage training paradigm, with soft instruction mechanism based on text descriptions for emotional tone guidance.
IndexTTS-2: Advanced Emotional Control and Duration Precision
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech (TTS) model designed to address the challenge of precise duration control in large-scale TTS systems, which is a significant limitation in applications like video dubbing. It introduces a novel, general method for speech duration control, supporting two modes: one that explicitly specifies the number of generated tokens for precise duration, and another that generates speech freely in an auto-regressive manner. Furthermore, IndexTTS2 achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts. To enhance speech clarity in highly emotional expressions, the model incorporates GPT latent representations and utilizes a novel three-stage training paradigm.
Pros
- Precise duration control for video dubbing applications.
- Independent control over timbre and emotional expression.
- Zero-shot voice cloning capabilities.
Cons
- Complex architecture may require technical expertise.
- Both input and output pricing at $7.15/M UTF-8 bytes on SiliconFlow.
Why We Love It
- It revolutionizes narration control with precise timing and emotional expression, making it ideal for professional video dubbing and expressive storytelling applications.
Text-to-Speech Model Comparison
In this table, we compare 2025's leading open source text-to-speech models for narration, each with unique strengths. Fish Speech V1.5 offers industry-leading quality with proven arena performance. CosyVoice2-0.5B excels in ultra-low latency streaming applications. IndexTTS-2 provides advanced emotional control and precise duration management. This side-by-side view helps you choose the right model for your specific narration requirements.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | Fish Speech V1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | Industry-leading quality & multilingual |
| 2 | CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | Ultra-low 150ms latency streaming |
| 3 | IndexTTS-2 | IndexTeam | Text-to-Speech | $7.15/M UTF-8 bytes | Emotional control & duration precision |
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 advanced narration control.
Our analysis shows different leaders for specific needs. Fish Speech V1.5 is the top choice for high-quality multilingual narration with proven performance. CosyVoice2-0.5B excels for real-time streaming applications requiring ultra-low latency. IndexTTS-2 is best for applications requiring precise duration control and emotional expression, such as video dubbing and expressive storytelling.