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F5-TTS-robot
ACloudCenter/F5-TTS-robot
F5-TTS-robot is a machine learning model from ACloudCenter. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Full finetune of F5TTSv1Base on ACloudCenter/robot-tts-corpus: ~1.7 h of synthetic robot speech in 6 styles (omnibot vocoder-buzz, terminator ring-mod android, scifi metallic, gruff, intercom PA, telephone narrowband)…
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Updated Sep 22, 2026
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Sep 22, 2026
- Updated
- Sep 22, 2026
- SHA
- deb0b146
Model card
From the Hugging Face model README
F5-TTS robot voices (finetuned)
Full finetune of F5TTS_v1_Base on ACloudCenter/robot-tts-corpus: ~1.7 h of synthetic robot speech in 6 styles (omnibot vocoder-buzz, terminator ring-mod android, scifi metallic, gruff, intercom PA, telephone narrowband), built from 5 LibriSpeech test-clean speakers.
12 epochs (~3900 updates), lr 1e-5, batch 1618 frames, vocab = Emilia pinyin.
Usage
The checkpoint is a full merged model (no PEFT needed):
from f5_tts.api import F5TTS
model = F5TTS(ckpt_file="model_last.pt", vocab_file="vocab.txt")
# ref_audio: a clip in the damaged style you want (see ACloudCenter/robot-tts-corpus refs/)
wav, sr, _ = model.infer(ref_file="ref_omnibot.wav", ref_text="<its transcript>", gen_text="Attention. Reactor core temperature exceeds tolerance.")
Pick the reference clip matching the style you want generated - the style identity comes entirely from the reference audio. Held-out reference clips per style are in ACloudCenter/robot-tts-corpus (refs/ + refs.csv).
- License
- apache-2.0
- Created
- Sep 22, 2026
- Updated
- Sep 22, 2026