OpenAudio S1 是 Fish Audio 最新推出的文本转语音（TTS）模型，基于超过 200 万小时的音频数据进行训练，旨在提供高度自然的语音合成体验.
主要特点
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自然流畅的语音：OpenAudio S1 生成的语音几乎与人类配音无异，适用于视频配音、播客和游戏角色语音等专业场景，提供高度自然的声音体验。
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丰富的情感和语气控制：该模型支持多种情感标记（如愤怒、快乐、悲伤等）和语调标记（如急促、低声、尖叫等），用户可以通过简单的文本命令来控制语音的情感和语气，使得合成的对话更加生动和个性化。
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多语言支持：OpenAudio S1 支持多达 13 种语言，包括英语、中文、日语、法语、德语等，展现出强大的多语言能力，适合全球用户使用。
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高效的语音克隆：该模型支持零样本和少样本语音克隆，只需 10 到 30 秒的音频样本即可生成高保真的克隆声音，适合快速生成个性化语音的场景。
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灵活的部署选项：OpenAudio S1 提供两种版本：完整版 S1（40 亿参数）和精简版 S1-mini（5 亿参数），后者为开源模型，适合研究和教育用途，而 S1 则通过云服务提供高性能支持，确保成本可控。
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经济实惠的定价：OpenAudio S1 的定价为每百万字节 15 美元（约 0.8 美元/小时），使得高质量的语音生成对开发者更加可及，尤其是对于高容量或预算有限的项目。
应用场景
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内容创作：OpenAudio S1 可以为视频、播客和有声书提供专业级的配音，显著提高制作效率。这使得内容创作者能够快速生成高质量的音频内容，满足市场需求。
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虚拟助手：该模型能够创建个性化的语音导航或客服系统，支持多种语言的交互，提升用户体验。通过自然流畅的语音，虚拟助手可以更好地理解和响应用户的需求。
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游戏与娱乐：OpenAudio S1 可以为游戏角色生成真实的对话和旁白，增强玩家的沉浸感。这种高质量的语音合成能够使游戏中的角色更加生动和可信。
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教育与培训：在教育领域，OpenAudio S1 可以用于生成多语言学习内容，帮助学生更好地理解和学习不同语言的发音和语调。
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客服与支持：该模型适用于客服机器人，能够提供快速、准确的语音回答，提升客户服务的效率和质量。
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实时应用：由于其超低延迟（低于 100 毫秒），OpenAudio S1 也非常适合实时应用，如在线游戏和直播内容，确保语音输出的即时性和流畅性。
OpenAudio S1 is the latest text-to-speech (TTS) model launched by Fish Audio. Trained on over 2 million hours of audio data, it aims to deliver a highly natural speech synthesis experience.
Key Features
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Natural and Fluent Speech:
OpenAudio S1 generates speech that is nearly indistinguishable from human voiceovers, making it suitable for professional use cases such as video narration, podcasts, and game character voices, offering a highly natural audio experience. -
Rich Emotion and Tone Control:
The model supports a wide range of emotional tags (e.g., angry, happy, sad) and tone modifiers (e.g., fast, whisper, shout). Users can control the emotion and tone of the speech using simple text commands, enabling more vivid and personalized dialogues. -
Multilingual Support:
OpenAudio S1 supports up to 13 languages, including English, Chinese, Japanese, French, and German, showcasing strong multilingual capabilities and catering to a global user base. -
Efficient Voice Cloning:
The model supports zero-shot and few-shot voice cloning. With just 10 to 30 seconds of audio samples, it can generate high-fidelity cloned voices, making it ideal for scenarios requiring rapid personalization. -
Flexible Deployment Options:
OpenAudio S1 comes in two versions: the full S1 model (4 billion parameters) and a lightweight open-source S1-mini version (500 million parameters). The former is offered via cloud services for high-performance needs, while the latter is suited for research and educational purposes. -
Affordable Pricing:
OpenAudio S1 is priced at $15 per million bytes (approximately $0.80/hour), making high-quality voice generation more accessible to developers, especially for high-volume or budget-sensitive projects.
Application Scenarios
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Content Creation:
OpenAudio S1 can provide professional-grade voiceovers for videos, podcasts, and audiobooks, significantly improving production efficiency. This allows content creators to quickly generate high-quality audio to meet market demands. -
Virtual Assistants:
The model can create personalized voice navigation or customer service systems with multilingual interaction, enhancing the user experience. Its natural speech enables virtual assistants to better understand and respond to user needs. -
Gaming and Entertainment:
OpenAudio S1 can generate realistic dialogue and narration for game characters, enhancing player immersion. Its high-quality speech synthesis makes in-game characters more vivid and believable. -
Education and Training:
In the education sector, OpenAudio S1 can be used to generate multilingual learning content, helping students better understand and learn pronunciation and intonation in different languages. -
Customer Service and Support:
The model is suitable for customer service bots, providing quick and accurate spoken responses, thereby improving service efficiency and quality. -
Real-Time Applications:
With ultra-low latency (under 100 milliseconds), OpenAudio S1 is also ideal for real-time applications such as online gaming and live content, ensuring immediate and smooth speech output.
