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Tokenizer for Text to Speech (TTS) models

Project description

ttstokenizer: Tokenizer for Text to Speech (TTS) models


See the original repository for more information on English Grapheme to Phoneme conversion.

Other than removing unused dependencies and reorganizing the files, the original logic remains unchanged

ttstokenizer makes it easy to feed text to speech models with minimal dependencies that are Apache 2.0 compatible.

The standard preprocessing logic for many English Text to Speech (TTS) models is as follows:

  • Apply Tacotron text normalization rules
    • This project replicates the logic found in ESPnet
  • Convert Graphemes to Phonemes
  • Build an integer array mapping Phonemes to their integer token positions

This project adds a new tokenizer that runs the logic above. The output is consumable by machine learning models.


The easiest way to install is via pip and PyPI

pip install ttstokenizer


An example of tokenizing text for TTS models is shown below.

from ttstokenizer import TTSTokenizer

tokenizer = TTSTokenizer(tokens)
print(tokenizer("Text to tokenize"))

>>> array([ 4, 15, 10,  6,  4,  4, 28,  4, 34, 10,  2,  3, 51, 11])

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