What are Open Source Real-Time Transcription Models?
Open source real-time transcription models are specialized AI systems that convert spoken language into text in real-time. Using advanced deep learning architectures, they process audio streams and deliver accurate text output with minimal latency. This technology enables developers and creators to build transcription services, voice assistants, and accessibility tools with unprecedented freedom. They foster collaboration, accelerate innovation, and democratize access to powerful speech recognition capabilities, enabling applications from live captioning to 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 evaluations by TTS Arena, the model achieved an ELO score of 1339, with exceptional accuracy rates: 3.5% WER and 1.2% CER for English, and 1.3% CER for Chinese characters.
Fish Speech V1.5: Multilingual Excellence in Speech Synthesis
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 achieved an ELO score of 1339, with exceptional accuracy rates: 3.5% WER and 1.2% CER for English, and 1.3% CER for Chinese characters.
Pros
- Exceptional accuracy with 3.5% WER for English.
- Innovative DualAR architecture design.
- Massive training dataset (300,000+ hours).
Cons
- Higher pricing at $15/M UTF-8 bytes on SiliconFlow.
- Primarily focused on TTS rather than transcription.
Why We Love It
- It delivers industry-leading accuracy with multilingual support, making it perfect for high-quality speech synthesis applications requiring exceptional precision.
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. Compared to version 1.0, pronunciation error rate reduced by 30%-50%, MOS score improved to 5.53, supporting Chinese dialects, English, Japanese, Korean with cross-lingual capabilities.
CosyVoice2-0.5B: Ultra-Low Latency Streaming Solution
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. The model enhances speech token codebook utilization through finite scalar quantization (FSQ) and features chunk-aware causal streaming. Compared to version 1.0, pronunciation error rate reduced by 30%-50%, MOS score improved to 5.53, supporting Chinese dialects, English, Japanese, Korean with cross-lingual capabilities.
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 0.5B parameter size compared to larger models.
- Primarily optimized for synthesis rather than transcription.
Why We Love It
- It strikes the perfect balance between speed and quality with 150ms latency, making it ideal for real-time applications requiring immediate response.
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 disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion. The model incorporates GPT latent representations and utilizes a novel three-stage training paradigm, outperforming state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity.
IndexTTS-2: Advanced Zero-Shot Speech Control
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech model designed to address precise duration control challenges in large-scale TTS systems. It introduces novel methods for speech duration control with two modes: explicit token generation 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, outperforming state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity across multiple datasets.
Pros
- Breakthrough zero-shot capabilities with duration control.
- Independent control over timbre and emotion.
- Superior performance in word error rate and speaker similarity.
Cons
- Complex architecture may require technical expertise.
- Focused on synthesis rather than direct transcription.
Why We Love It
- It offers unprecedented control over speech generation with zero-shot capabilities, perfect for applications requiring precise emotional and temporal control.
AI Model Comparison
In this table, we compare 2025's leading open source models for real-time transcription and speech synthesis, each with unique strengths. Fish Speech V1.5 provides exceptional multilingual accuracy, CosyVoice2-0.5B offers ultra-low latency streaming, while IndexTTS-2 delivers advanced zero-shot control capabilities. This side-by-side view helps you choose the right tool for your specific transcription or 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 | Exceptional multilingual accuracy |
| 2 | CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | Ultra-low latency (150ms) |
| 3 | IndexTTS-2 | IndexTeam | Audio | $7.15/M UTF-8 bytes | Zero-shot 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 real-time speech processing and text-to-speech synthesis with exceptional accuracy and low latency.
Our analysis shows different leaders for specific needs. Fish Speech V1.5 is the top choice for multilingual accuracy with exceptional error rates. CosyVoice2-0.5B excels for real-time applications requiring ultra-low latency of 150ms. IndexTTS-2 is best for applications needing precise control over speech generation with zero-shot capabilities.