What are Open Source AI Models for Voice Assistants?
Open source AI models for voice assistants are specialized text-to-speech (TTS) systems that convert written text into natural-sounding speech. Using advanced deep learning architectures like transformers and autoregressive models, they enable developers to create voice interfaces with human-like speech synthesis. This technology allows businesses and creators to build conversational AI, multilingual voice applications, and accessible speech solutions with unprecedented freedom. They foster collaboration, accelerate innovation, and democratize access to powerful voice technologies, enabling a wide range of applications from virtual assistants 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 TTS Arena evaluations, it achieved an exceptional ELO score of 1339, with impressive accuracy rates: 3.5% WER and 1.2% CER for English, and 1.3% CER for Chinese characters.
Fish Speech V1.5: Leading Multilingual Voice 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 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, making it ideal for multilingual voice assistant applications.
Pros
- Innovative DualAR architecture with dual autoregressive transformers.
- Exceptional multilingual support (English, Chinese, Japanese).
- Top-tier performance with ELO score of 1339 in TTS Arena.
Cons
- Higher pricing compared to other TTS models.
- May require technical expertise for optimal implementation.
Why We Love It
- It delivers industry-leading multilingual voice synthesis with exceptional accuracy, making it perfect for global voice assistant applications.
CosyVoice2-0.5B
CosyVoice 2 is a streaming speech synthesis model based on large language model architecture, featuring a unified streaming/non-streaming framework. It achieves ultra-low latency of 150ms in streaming mode while maintaining high synthesis quality. Compared to version 1.0, pronunciation error rates are reduced by 30%-50%, MOS score improved from 5.4 to 5.53, with fine-grained emotion and dialect control. Supports Chinese (including dialects), English, Japanese, Korean, and cross-lingual scenarios.
CosyVoice2-0.5B: Ultra-Low Latency Streaming Speech
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. In streaming mode, it achieves ultra-low latency of 150ms while maintaining synthesis quality almost identical to non-streaming mode. Compared to version 1.0, the pronunciation error rate has been reduced by 30%-50%, the MOS score improved from 5.4 to 5.53, and supports fine-grained control over emotions and dialects.
Pros
- Ultra-low latency of 150ms in streaming mode.
- 30%-50% reduction in pronunciation error rates.
- Improved MOS score from 5.4 to 5.53.
Cons
- Smaller parameter size may limit complex voice generation.
- Primarily optimized for Asian languages.
Why We Love It
- It combines real-time streaming capabilities with exceptional quality, perfect for responsive voice assistant interactions with minimal delay.
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 control over timbre and emotion via separate prompts. The model incorporates GPT latent representations and utilizes a novel three-stage training paradigm, with soft instruction mechanism for emotional control based on text descriptions.
IndexTTS-2: Zero-Shot Emotional Voice 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. It introduces a novel method for speech duration control, supporting 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 control over timbre and emotion via separate prompts. It incorporates GPT latent representations and utilizes a novel three-stage training paradigm, with a soft instruction mechanism based on text descriptions for effective emotional tone guidance.
Pros
- Zero-shot capability with no fine-tuning required.
- Precise duration control for applications like video dubbing.
- Independent control over timbre and emotional expression.
Cons
- Requires input pricing in addition to output costs.
- More complex setup due to advanced emotional control features.
Why We Love It
- It revolutionizes voice assistant emotional intelligence with zero-shot learning and precise control over speech characteristics and timing.
Voice Assistant AI Model Comparison
In this table, we compare 2025's leading open source AI models for voice assistants, each with unique strengths. For multilingual applications, Fish Speech V1.5 provides exceptional accuracy. For real-time interactions, CosyVoice2-0.5B offers ultra-low latency streaming. For emotional voice control, IndexTTS-2 delivers zero-shot capabilities. This side-by-side view helps you choose the right model for your voice assistant project.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | Fish Speech V1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | Multilingual accuracy leader |
| 2 | CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | Ultra-low latency streaming |
| 3 | IndexTTS-2 | IndexTeam | Text-to-Speech | $7.15/M UTF-8 bytes | Zero-shot emotional 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 text-to-speech synthesis and voice assistant applications.
Our analysis shows different leaders for various needs. Fish Speech V1.5 is ideal for multilingual voice assistants requiring high accuracy across languages. CosyVoice2-0.5B is perfect for real-time conversational assistants needing minimal latency. IndexTTS-2 excels in applications requiring emotional intelligence and precise duration control, such as interactive storytelling or advanced customer service bots.