Skip to content

eldntr/PL-BERT-ID

 
 

Repository files navigation

PL-BERT-ID

Prerequisites

  • Python 3.13
  • Linux/macOS/Windows
  • espeak-ng (for text-to-speech functionality)

Installation

1. Install System Dependencies

Linux:

sudo apt update
sudo apt install espeak-ng

macOS:

brew install espeak-ng

Windows: Download and install from espeak-ng releases

2. Install UV Package Manager

curl -LsSf https://astral.sh/uv/install.sh | sh

3. Create Virtual Environment

# Create virtual environment using uv
uv venv -p 3.13

# Activate virtual environment
# Linux/macOS
source .venv/bin/activate

# Windows
.venv\Scripts\activate

4. Install Project Dependencies

# Install in editable mode (recommended for development)
uv pip install -e .

# Or sync dependencies from lock file
uv sync

Dataset Setup

Download Wikipedia Indonesian Dataset

  1. Create a wikipedia.id folder in the project root:

    mkdir -p wikipedia.id
  2. Download the parquet file from HuggingFace:

Usage

Training Pipeline

  1. Preprocess the data:

    python preprocessing.py
  2. Train the model:

    python train.py

About

Phoneme-Level BERT for Enhanced Prosody of Text-to-Speech with Grapheme Predictions

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages

  • Python 100.0%