What are Open Source Speech-to-Text Models?
Open source speech-to-text models are specialized AI systems that convert written text into natural-sounding speech using advanced deep learning architectures. These text-to-speech (TTS) models use neural networks to transform textual input into high-quality audio output with human-like pronunciation, intonation, and emotion. They enable developers and creators to build voice applications, accessibility tools, and multimedia content with unprecedented flexibility. By being open source, they foster collaboration, accelerate innovation, and democratize access to powerful speech synthesis technology, supporting applications from virtual assistants to video dubbing and multilingual communication systems.
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. With an ELO score of 1339 in TTS Arena evaluations, it achieved a word error rate of 3.5% and character error rate of 1.2% for English, and 1.3% CER for Chinese characters.
Fish Speech V1.5: Leading Multilingual Speech Synthesis
Fish Speech V1.5 represents the cutting edge of open-source text-to-speech technology with its innovative DualAR architecture featuring dual autoregressive transformer design. The model demonstrates exceptional performance across multiple languages, trained on massive datasets including over 300,000 hours for both English and Chinese, and over 100,000 hours for Japanese. In independent TTS Arena evaluations, it achieved an outstanding ELO score of 1339, with remarkably low error rates: 3.5% word error rate (WER) and 1.2% character error rate (CER) for English, and 1.3% CER for Chinese characters. This performance makes it ideal for multilingual applications requiring high-quality speech synthesis.
Pros
- Innovative DualAR architecture with dual autoregressive transformers.
- Exceptional multilingual support (English, Chinese, Japanese).
- Outstanding TTS Arena performance with 1339 ELO score.
Cons
- Limited to three main languages compared to some competitors.
- May require significant computational resources for optimal performance.
Why We Love It
- It delivers industry-leading performance in multilingual speech synthesis with proven low error rates and innovative architecture that sets the standard for open-source TTS models.
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 v1.0, it reduces pronunciation errors by 30-50%, improves MOS score from 5.4 to 5.53, and supports fine-grained emotion and dialect control across Chinese, English, Japanese, Korean, and cross-lingual scenarios.
CosyVoice2-0.5B: Ultra-Low Latency Streaming Speech Synthesis
CosyVoice 2 represents a breakthrough in streaming speech synthesis with its large language model foundation and unified streaming/non-streaming framework design. The model enhances speech token codebook utilization through finite scalar quantization (FSQ) and features a chunk-aware causal streaming matching model supporting diverse synthesis scenarios. In streaming mode, it achieves remarkable ultra-low latency of 150ms while maintaining synthesis quality virtually identical to non-streaming mode. Compared to version 1.0, the model shows significant improvements: 30-50% reduction in pronunciation error rates, MOS score improvement from 5.4 to 5.53, and fine-grained control over emotions and dialects. It supports Chinese (including Cantonese, Sichuan, Shanghainese, Tianjin dialects), English, Japanese, Korean, with cross-lingual and mixed-language capabilities.
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 parameter size (0.5B) may limit some advanced capabilities.
- Streaming optimization may require specific technical implementation.
Why We Love It
- It perfectly balances speed and quality with ultra-low latency streaming while supporting extensive multilingual and dialect capabilities with fine-grained emotional control.
IndexTTS-2
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech model designed for precise duration control, addressing key limitations in applications like video dubbing. It features novel speech duration control with 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 timbre and emotion control via separate prompts, and outperforms state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity.
IndexTTS-2: Zero-Shot TTS with Precise Duration Control
IndexTTS2 represents a revolutionary advancement in auto-regressive zero-shot Text-to-Speech technology, specifically designed to address the critical challenge of precise duration control in large-scale TTS systems—a significant limitation in applications like video dubbing. The model introduces a novel, general method for speech duration control, supporting two distinct modes: one that explicitly specifies the number of generated tokens for precise duration matching, and another that generates speech freely in an auto-regressive manner. A key innovation is the disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion through separate prompts. To enhance speech clarity in highly emotional expressions, IndexTTS2 incorporates GPT latent representations and utilizes a sophisticated three-stage training paradigm. The model features a soft instruction mechanism based on text descriptions, developed by fine-tuning Qwen3, to effectively guide emotional tone generation. Experimental results demonstrate that IndexTTS2 outperforms state-of-the-art zero-shot TTS models across multiple datasets in word error rate, speaker similarity, and emotional fidelity.
Pros
- Breakthrough precise duration control for video dubbing applications.
- Independent control over timbre and emotion via separate prompts.
- Superior performance in word error rate and speaker similarity.
Cons
- Complex architecture may require advanced technical expertise.
- Three-stage training paradigm increases computational requirements.
Why We Love It
- It solves the critical duration control problem for professional applications while offering unprecedented independent control over speaker identity and emotional expression.
Speech-to-Text Model Comparison
In this table, we compare 2025's leading open source text-to-speech models, each with unique strengths. For multilingual excellence, Fish Speech V1.5 provides exceptional accuracy. For ultra-low latency streaming, CosyVoice2-0.5B offers unmatched speed with quality. For precise duration control and emotional expression, IndexTTS-2 delivers professional-grade capabilities. This side-by-side view helps you choose the right model for your specific speech synthesis requirements.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | Fish Speech V1.5 | fishaudio | Text-to-Speech | $15/ M UTF-8 bytes | Multilingual accuracy with 1339 ELO score |
| 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 | Precise duration control & emotion |
Frequently Asked Questions
Our top three picks for 2025 are Fish Speech V1.5, CosyVoice2-0.5B, and IndexTTS-2. Each of these text-to-speech models stood out for their innovation, performance, and unique approach to solving challenges in speech synthesis, multilingual support, streaming capabilities, and duration control.
Our analysis shows different leaders for various needs. Fish Speech V1.5 is ideal for multilingual applications requiring high accuracy. CosyVoice2-0.5B excels in real-time streaming applications with its 150ms latency. IndexTTS-2 is perfect for professional content creation requiring precise duration control and emotional expression, particularly in video dubbing and media production.