SteerTTS：2300万参数可调控英语TTS发布
AI 总结
开发者 WhissleAI 在 r/MachineLearning 发布 SteerTTS，一个总参数约 2300 万的英语 TTS 模型：9.6M 参数声学模型加 Vocos 声码器，可通过 12 个以 z-score 表示的数值控制语速、响度和音高等。帖子称它在 RTX 5070 上 RTFx 约 60–80，在 CPU 上约 4–8，并支持 2825 个内置音色、51 个风格标签和句级流式输出。开发者同时承认暂停、发声等控制较弱，情感标签区分度有限，克隆相似度低，且尚无人工评测；权重采用 CC BY-NC 4.0、代码采用 MIT。
深度见解
开发者称其动机是填补小型、可调控 TTS 模型的空白，以便在对话中由 LLM 按上下文提供控制参数。
I was looking for small TTS model which is steerable but couldn't find any, specially something I can adjust contextually by providing controls from LLM during a conversation. So I built one.
What it is:
- 9.6M-param acoustic model (attention + bidirectional Mamba-3, FastPitch-style) + Vocos vocoder = 23M total
- 12 controls, each a z-score relative to the chosen voice’s own neutral speech: rate, loudness, median pitch, pitch range, final rise/fall, pauses, spectral tilt, breathiness-related measures.
- Also: 51 style tags, free-text prompts (resolved into an inspectable JSON request), inline markup (
*emphasis*,[pause 400ms],<slow>…</slow>), sentence-level streaming - 2,825 built-in (anonymized) voices, plus experimental zero-shot cloning
Speed:
- RTFx ~60–80 on an RTX 5070 - ~4–8 on CPU without the optional flow refiner. First streamed audio in ~0.5 s on CPU.
Quality: