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<a name="introduction"></a> XPhoneBERT : A Pre-trained Multilingual Model for Phoneme Representations for Text-to-Speech

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.

The general architecture and experimental results of XPhoneBERT can be found in our INTERSPEECH 2023 paper:

Please CITE our paper when XPhoneBERT is used to help produce published results or is incorporated into other software.

For further information or requests, please go to XPhoneBERT's homepage!

<a name="transformers"></a> Using XPhoneBERT with transformers

Installation <a name="install2"></a>

• Install transformers with pip: pip install transformers, or install transformers from source.

• Install text2phonemesequence: pip install text2phonemesequence <br> Our text2phonemesequence package is to convert text sequences into phoneme-level seque

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