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khanomtan-tts-v1.0

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wannaphong commited on Aug 24, 2022

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@@ -4,9 +4,9 @@ license: apache-2.0
 # KhanomTan TTS v1.0
-KhnomTan TTS (ขนมตาล) is a open-source Thai text-to-speech model that supports multilingual speakers. It supports Thai, English, and others.
-KhnomTan TTS is a YourTTS model that trained with supports Thai. We add the Thai speech corpus from TSync 1* and TSync 2* to [mbarnig/lb-de-fr-en-pt-12800-TTS-CORPUS](https://huggingface.co/datasets/mbarnig/lb-de-fr-en-pt-12800-TTS-CORPUS) that train the model with YourTTS model.
 ## Config
 We have Thai characters to the graphemes config for training the model and use the Speaker Encoder model from the speaker encoder model from [🐸 Coqui-TTS](https://github.com/coqui-ai/TTS/releases/tag/speaker_encoder_model).
@@ -17,8 +17,8 @@ We add Tsync 1 corpus and Tsync 2 corpus, which are not complete datasets, and t
 ## Trained the model
 We use the 🐸 Coqui-TTS multilingual VITS-model recipe (version 0.7.1 or the commit id is d46fbc240ccf21797d42ac26cb27eb0b9f8d31c4) for training the model, and we use the speaker encoder model from [🐸 Coqui-TTS](https://github.com/coqui-ai/TTS/releases/tag/speaker_encoder_model) then we release the best model to public access.
-Model cards: ____
-Dataset (Tsync 1 and Tsync 2 only): ____
-GitHub: ____
 *Note: Those are not complete corpus. We can access the public corpus only.

 # KhanomTan TTS v1.0
+KhanomTan TTS (ขนมตาล) is a open-source Thai text-to-speech model that supports multilingual speakers. It supports Thai, English, and others.
+KhanomTan TTS is a YourTTS model that trained with supports Thai. We add the Thai speech corpus from TSync 1* and TSync 2* to [mbarnig/lb-de-fr-en-pt-12800-TTS-CORPUS](https://huggingface.co/datasets/mbarnig/lb-de-fr-en-pt-12800-TTS-CORPUS) that train the model with YourTTS model.
 ## Config
 We have Thai characters to the graphemes config for training the model and use the Speaker Encoder model from the speaker encoder model from [🐸 Coqui-TTS](https://github.com/coqui-ai/TTS/releases/tag/speaker_encoder_model).
 ## Trained the model
 We use the 🐸 Coqui-TTS multilingual VITS-model recipe (version 0.7.1 or the commit id is d46fbc240ccf21797d42ac26cb27eb0b9f8d31c4) for training the model, and we use the speaker encoder model from [🐸 Coqui-TTS](https://github.com/coqui-ai/TTS/releases/tag/speaker_encoder_model) then we release the best model to public access.
+- Model cards: [https://github.com/wannaphong/KhanomTan-TTS-v1.0](https://github.com/wannaphong/KhanomTan-TTS-v1.0)
+- Dataset (Tsync 1 and Tsync 2 only): [https://huggingface.co/datasets/wannaphong/tsync1-2-yourtts](https://huggingface.co/datasets/wannaphong/tsync1-2-yourtts)
+- GitHub: [https://github.com/wannaphong/KhanomTan-TTS-v1.0](https://github.com/wannaphong/KhanomTan-TTS-v1.0)
 *Note: Those are not complete corpus. We can access the public corpus only.