What are Open Source Speech Recognition Models?
Open source speech recognition models are specialized AI systems that convert text into natural-sounding speech with remarkable speed and accuracy. Using advanced deep learning architectures like autoregressive transformers and streaming frameworks, they enable real-time speech synthesis for multiple languages and dialects. This technology allows developers and creators to build voice applications, interactive systems, and audio content with unprecedented efficiency. 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 solutions.
CosyVoice2-0.5B
CosyVoice 2 is a streaming speech synthesis model based on a large language model, employing a unified streaming/non-streaming framework design. 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.
CosyVoice2-0.5B: Ultra-Low Latency Speech Synthesis
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. The model supports Chinese (including dialects: Cantonese, Sichuan dialect, Shanghainese, Tianjin dialect, etc.), English, Japanese, Korean, and supports cross-lingual and mixed-language scenarios.
Pros
- Ultra-low latency of 150ms in streaming mode.
- 30%-50% reduction in pronunciation error rate.
- Improved MOS score from 5.4 to 5.53.
Cons
- Smaller parameter count may limit complexity.
- Streaming quality slightly different from non-streaming.
Why We Love It
- It delivers industry-leading speed with 150ms latency while maintaining exceptional quality, making it perfect for real-time applications.
fishaudio/fish-speech-1.5
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 both English and Chinese, and over 100,000 hours for Japanese. The model achieved exceptional performance with an ELO score of 1339 in TTS Arena evaluations.
fishaudio/fish-speech-1.5: Premium Multilingual Speech Synthesis
Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model. The model employs an innovative DualAR architecture, featuring a dual autoregressive transformer design. It supports multiple languages, with over 300,000 hours of training data for both 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
- Innovative DualAR architecture for superior performance.
- Massive training dataset with 300,000+ hours.
- Exceptional ELO score of 1339 in TTS Arena.
Cons
- Higher pricing at $15/M UTF-8 bytes on SiliconFlow.
- May require more computational resources.
Why We Love It
- It combines cutting-edge DualAR architecture with massive multilingual training data to deliver top-tier speech synthesis quality.
IndexTTS-2
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech (TTS) model designed for precise duration control in large-scale TTS systems. It achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts. The model outperforms state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity.
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. 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 emotion.
- Zero-shot capability with superior performance.
Cons
- Complex architecture may require technical expertise.
- Both input and output pricing on SiliconFlow.
Why We Love It
- It revolutionizes speech synthesis with precise duration control and emotional disentanglement, perfect for professional video dubbing and creative applications.
Speech Recognition AI Model Comparison
In this table, we compare 2025's leading open source speech recognition models, each with a unique strength. For ultra-fast streaming, CosyVoice2-0.5B provides 150ms latency. For premium multilingual synthesis, fishaudio/fish-speech-1.5 offers top-tier quality with massive training data, while IndexTTS-2 prioritizes emotional control and duration precision. This side-by-side view helps you choose the right tool for your specific speech synthesis goal.
| Number | Model | Developer | Subtype | SiliconFlow Pricing | Core Strength |
|---|---|---|---|---|---|
| 1 | CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | Ultra-low 150ms latency |
| 2 | fishaudio/fish-speech-1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | Premium multilingual quality |
| 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 CosyVoice2-0.5B, fishaudio/fish-speech-1.5, and IndexTTS-2. Each of these models stood out for their speed optimization, multilingual capabilities, and unique approach to solving challenges in text-to-speech synthesis and real-time speech generation.
Our in-depth analysis shows CosyVoice2-0.5B is the top choice for real-time applications with its 150ms ultra-low latency in streaming mode. For applications requiring the highest quality multilingual synthesis, fishaudio/fish-speech-1.5 with its DualAR architecture is optimal. For video dubbing and applications needing emotional control, IndexTTS-2 provides the best balance of speed and precision.