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Bokhbat/mongolian-vits-tts:
the multi-speaker Mongolian VITS model with one new voice (speaker01) added,
without degrading the original Mongolian ability.speaker01 (id 78, the new voice)text_encoder (phonetics/text) and duration_predictor (rhythm/prosody)
were frozen — the language model cannot drift on the small dataset.2e-5 (base used 2e-4) + eval-based best-model selection.speaker01
is the newly learned voice. Note: 3.7 min is very little data — speaker01
is recognizable but rough; more data would sharpen it.| File | Description |
|---|---|
best_model.pth | Fine-tuned VITS checkpoint (79 speakers) |
config.json | Coqui TTS config |
speakers.pth | 79-speaker name→id map (speaker01 = 78) |
tensorboard/ | Fine-tune training curves |
ft_yourvoice_spk01.wav | Sample: new voice (speaker01) |
ft_original_spk0053.wav | Sample: an original voice (spk_0053), Mongolian-ability check |
1from huggingface_hub import hf_hub_download
2from TTS.utils.synthesizer import Synthesizer
3
4repo = "Bokhbat/mongolian-vits-myvoice"
5ckpt = hf_hub_download(repo, "best_model.pth")
6cfg = hf_hub_download(repo, "config.json")
7spk = hf_hub_download(repo, "speakers.pth")
8
9syn = Synthesizer(ckpt, cfg, tts_speakers_file=spk, use_cuda=False)
10# the new voice:
11wav = syn.tts("Сайн байна уу?", speaker_name="speaker01")
12syn.save_wav(wav, "myvoice.wav")
13# an original Mongolian voice still works:
14wav = syn.tts("Сайн байна уу?", speaker_name="spk_0053")
15syn.save_wav(wav, "original.wav")