What are Open Source AI Models for On-Device Transcription?
Open source AI models for on-device transcription are specialized neural networks that convert speech to text and text to speech directly on your device, without requiring cloud connectivity. Using deep learning architectures like autoregressive transformers and advanced speech synthesis techniques, they process audio data with exceptional accuracy and low latency. This technology allows developers and creators to build transcription applications, voice interfaces, and accessibility tools with unprecedented freedom. They foster collaboration, accelerate innovation, and democratize access to powerful speech processing capabilities, enabling a wide range of applications from real-time captioning to voice assistants and multilingual communication systems.
Fish Speech V1.5
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.
Fish Speech V1.5: Leading Multilingual TTS with Exceptional Accuracy
Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model that employs an innovative DualAR architecture, featuring a dual autoregressive transformer design. Trained on over 300,000 hours of data for English and Chinese, and over 100,000 hours for Japanese, it delivers exceptional performance across multiple languages. In independent evaluations by TTS Arena, the model achieved an impressive ELO score of 1339. The model demonstrates industry-leading accuracy with a word error rate (WER) of just 3.5% and a character error rate (CER) of 1.2% for English, and a CER of 1.3% for Chinese characters. This makes it ideal for high-quality on-device transcription and speech synthesis applications. Pricing on SiliconFlow is $15 per million UTF-8 bytes.
Pros
- Exceptional accuracy with 3.5% WER for English.
- Innovative DualAR architecture for superior performance.
- Massive training dataset (300,000+ hours).
Cons
- Higher pricing compared to other alternatives on SiliconFlow.
- Primarily focused on three languages.
Why We Love It
- It delivers unmatched accuracy and natural speech quality through its innovative DualAR architecture, making it the gold standard for multilingual on-device transcription.
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 Streaming 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. 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. The model supports Chinese (including dialects: Cantonese, Sichuan dialect, Shanghainese, Tianjin dialect, etc.), English, Japanese, Korean, and supports cross-lingual and mixed-language scenarios. Pricing on SiliconFlow is $7.15 per million UTF-8 bytes.
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 model may have limitations.
- Requires streaming infrastructure for optimal performance.
Why We Love It
- It combines ultra-low latency streaming with exceptional quality and emotion control, making it perfect for real-time on-device transcription and voice applications.
IndexTTS-2
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. It introduces a novel method for speech duration control and achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts. Experimental results show that IndexTTS2 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 and Emotion Control
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. To lower the barrier for emotional control, it also features a soft instruction mechanism based on text descriptions, developed by fine-tuning Qwen3, to effectively guide the generation of speech with the desired emotional tone. Experimental results show that IndexTTS2 outperforms state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity across multiple datasets. Pricing on SiliconFlow is $7.15 per million UTF-8 bytes.
Pros
- Precise duration control for applications like dubbing.
- Zero-shot capability for any voice without training.
- Independent control over emotion and speaker identity.
Cons
- More complex configuration for advanced features.
- May require fine-tuning for specific use cases.
Why We Love It
- It revolutionizes speech synthesis with precise duration control and emotion disentanglement, making it ideal for sophisticated on-device transcription and dubbing applications.
AI Model Comparison
In this table, we compare 2025's leading open source AI models for on-device transcription, each with a unique strength. For exceptional multilingual accuracy, Fish Speech V1.5 provides industry-leading performance. For real-time streaming with ultra-low latency, CosyVoice2-0.5B offers unmatched speed and quality, while IndexTTS-2 prioritizes precise duration control and zero-shot capabilities. This side-by-side view helps you choose the right tool for your specific transcription or speech synthesis goal.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | Fish Speech V1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | Exceptional accuracy (3.5% WER) |
| 2 | CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | Ultra-low latency (150ms) |
| 3 | IndexTTS-2 | IndexTeam | Text-to-Speech | $7.15/M UTF-8 bytes | Precise duration & emotion 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 on-device transcription, text-to-speech synthesis, and multilingual speech processing.
Our in-depth analysis shows several leaders for different needs. Fish Speech V1.5 is the top choice for applications requiring exceptional accuracy and multilingual support. For real-time streaming transcription with minimal latency, CosyVoice2-0.5B is the best option at just 150ms. For creators who need precise duration control and emotion management in voice synthesis, IndexTTS-2 delivers superior zero-shot capabilities.