SteerTTS Edge packs steerable English TTS into 11.84 MB
Developer /u/Working_Hat5120 released SteerTTS Edge, an 11.84 MB application payload containing model weights, voices, text front end, and Python runtime. Its 9.25M-parameter acoustic model and 6.2M-parameter Vocos-style vocoder use int4 quantization-aware training, while the text front end relies only on NumPy at runtime. The developer reports unchanged Seed-TTS WER at 0.96%, an approximately 0.1 UTMOS decline to 4.11, and at least 95% of each fp32 control’s effect across 12 steering controls in local Open TTS Leaderboard-protocol testing that was not officially submitted.
SteerTTS Edge is a compact release for applications needing steerable English speech with an 11.84 MB footprint, although its quality and control-retention results come from the developer’s local evaluation rather than an official leaderboard submission.
A while back I posted SteerTTS v1, a small English TTS you steer with numbers (https://huggingface.co/WhissleAI/steer-tts). Today I am releasing the edge variant:
https://huggingface.co/WhissleAI/steer-tts-edge
Size: everything an app has to ship (weights, voices, text front end and Python runtime) totals 11.84 MB.
How:
- Acoustic model (9.25M params, attention + bidirectional Mamba-3) is quantization-aware trained to int4
- 6.2M-param Vocos-style vocoder is distilled from
charactr/vocos-mel-24khz, also int4 QAT - Text front end is pure numpy, with no NLTK, g2p_en, torchaudio or num2words at runtime
Quality (Open TTS Leaderboard protocol, run locally, not an official submission):