Grapheme to Phoneme (G2P) with Stress

This project provides a Grapheme to Phoneme (G2P) conversion tool that first checks the CMU Pronouncing Dictionary for phoneme translations. If a word is not found in the dictionary, it utilizes two Transformer-based models to generate phoneme translations and add stress markers. The output is in ARPAbet format, and the model can also convert graphemes into phoneme integer indices.

Features

1. CMU Pronouncing Dictionary Integration: First checks the CMU dictionary for phoneme translations.
2. Transformer-Based Conversion:
   • Phoneme Generation: The first Transformer model converts graphemes into phonemes.
   • Stress Addition: The second Transformer model adds stress markers to the phonemes.
3. ARPAbet Output: Outputs phonemes in ARPAbet format.
4. Phoneme Integer Indices: Converts graphemes to phoneme integer indices.
5. A BPE tokenizer was used, which led to a better translation quality

Installation

1. Clone the repository:

   git clone https://github.com/NikiPshg/Grapheme-to-Phoneme-G2P-with-Stress.git
   cd Grapheme-to-Phoneme-G2P-with-Stress

2. Install the required dependencies:

   pip install -r requiremenst.txt

Example

from G2P_lexicon import g2p_en_lexicon

# Initialize the G2P converter
g2p = g2p_en_lexicon()
# Convert a word to phonemes
text = "text, numbers, and some strange symbols !№;% 21"
phonemes = g2p(text, with_stress=False)
['T', 'EH', 'K', 'S', 'T', ' ', ',',
 ' ', 'N', 'AH', 'M', 'B', 'ER', 'Z', ' ', ',',
 ' ', 'AE', 'N', 'D', ' ', 'S', 'AH', 'M', ' ',
 'S', 'T', 'R', 'EY', 'N', 'JH', ' ',
 'S', 'IH', 'M', 'B', 'AH', 'L', 'Z',
 ' ', '!', ' ', ';', ' ',
 'T', 'W', 'EH', 'N', 'IY', ' ', 'W', 'AH', 'N']

if you have any questions or you have found a bug, write here

https://t.me/Hophoppop