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  # <a name="introduction"></a> XPhoneBERT : A Pre-trained Multilingual Model for Phoneme Representations for Text-to-Speech
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  XPhoneBERT is the first pre-trained multilingual model for phoneme representations for text-to-speech(TTS). XPhoneBERT has the same model architecture as BERT-base, trained using the RoBERTa pre-training approach on 330M phoneme-level sentences from nearly 100 languages and locales. Experimental results show that employing XPhoneBERT as an input phoneme encoder significantly boosts the performance of a strong neural TTS model in terms of naturalness and prosody and also helps produce fairly high-quality speech with limited training data.
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  with torch.no_grad():
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  features = xphonebert(**input_ids)
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- ```
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+ ---
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+ license: mit
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+ ---
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  # <a name="introduction"></a> XPhoneBERT : A Pre-trained Multilingual Model for Phoneme Representations for Text-to-Speech
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  XPhoneBERT is the first pre-trained multilingual model for phoneme representations for text-to-speech(TTS). XPhoneBERT has the same model architecture as BERT-base, trained using the RoBERTa pre-training approach on 330M phoneme-level sentences from nearly 100 languages and locales. Experimental results show that employing XPhoneBERT as an input phoneme encoder significantly boosts the performance of a strong neural TTS model in terms of naturalness and prosody and also helps produce fairly high-quality speech with limited training data.
 
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  with torch.no_grad():
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  features = xphonebert(**input_ids)
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+ ```