st9-8/Forced-Alignment-Toolkit

Set of tools which will help for build forced alignment system for low resource languages. ## Forced Alignment Toolkit for Low-Resource Languages This repository gathers tools and datasets to support building forced alignment systems for low-resource languages. Our current focus is producing grapheme-to-phoneme (G2P) models in IPA using Montreal Forced Aligner. ## Languages - Baca — collecting and curating lexicon data prior to MFA G2P training. - Ewondo — preparing orthographic resources and cleaning pronunciation data. - Fulfulde — scraping Webonary lexicons and converting entries to IPA. - Wolof — adapting an existing MFA-compatible G2P model from the Kallaama dataset. ## Getting Started 1. Install Montreal Forced Aligner following the official instructions. 2. Review each language folder for data preparation notes and scripts. 3. Use MFA to train or adapt language-specific IPA G2P models as resources become available. ## Roadmap - Gather and normalize lexicons for every target language. - Train and validate MFA G2P models. - Package pronunciation dictionaries for downstream forced alignment experiments.