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Tortoise TTS AR model fine-tuned for German |
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Trained on 3 speakers; 2 LibriVox readers, and Thorsten Mueller's dataset https://github.com/thorstenMueller/Thorsten-Voice |
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***THE NEWEST VERSIONS***: v# indicates the number of training sessions, #e is how many epochs. |
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9/5 training session uploaded |
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Requires the tokenizer file placed in the tokenizers/ directory |
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Voice latents are pre-computed in voices/ for some uploaded versions. Voice samples to recompute latents are uploaded. |
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For use in MRQ Voice Cloning WebUI: |
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Requires the tokenizer used in training, and code changes to disable text cleaners. At minimum, change english_cleaners to basic_cleaners. |
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Code changes: |
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modules\tortoise-tts\tortoise\utils\tokenizer.py |
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Change Line 201: txt = english_cleaners(txt) and replace it |
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with txt = basic_cleaners(txt) |
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modules\tortoise-tts\build\lib\tortoise\utils\tokenizer.py |
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Change Line 201: txt = english_cleaners(txt) and replace it |
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with txt = basic_cleaners(txt) |
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\modules\dlas\dlas\data\audio\paired_voice_audio_dataset.py |
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Line 133: return text_to_sequence(txt, ['english_cleaners']) |
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and replace it with: return text_to_sequence(txt, ['basic_cleaners']) |
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modules\dlas\dlas\data\audio\voice_tokenizer.py |
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Line 14: from dlas.models.audio.tts.tacotron2.text.cleaners import |
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english_cleaners |
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to: from dlas.models.audio.tts.tacotron2.text.cleaners import |
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english_cleaners, basic_cleaners |
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Line 85: txt = english_cleaners(txt) to txt = |
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basic_cleaners(txt) |
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Line 134: word = english_cleaners(word) to basic_cleaners(word) |
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Copy and paste German text into the tokenizer tester on the utilities |
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tab, and you should see it tokenized with all of the special |
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characters, and no [UNK]. |
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--- |
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license: other |
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language: |
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- de |
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--- |