Benchmarking the Unsupervised Discovery of Phoneme Inventories With Discrete Speech Units
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DiscoPhon is a multilingual benchmark evaluating unsupervised phoneme discovery from discrete speech units. Given only 10 hours of speech in an unseen language, models must produce discrete units that map to a predefined phoneme inventory.
Getting started
DiscoPhon requires Python ≥ 3.12 and has no system dependencies.
- Install this package:
pip install discophon # core: data preparation and phoneme discovery pip install discophon[abx] # adds ABX discriminability (fastabx) pip install discophon[baselines] # adds the baseline models
- Follow the tutorials to download data, evaluate models, and prepare your submission.
- Current leaderboard.
References
@inproceedings{poli2026discophon,
title = {{DiscoPhon: Benchmarking the Unsupervised Discovery of Phoneme Inventories With Discrete Speech Units}},
author = {Maxime Poli and Manel Khentout and Angelo {Ortiz Tandazo} and Ewan Dunbar and Emmanuel Chemla and Emmanuel Dupoux},
year = {2026},
booktitle = {{Interspeech 2026}},
pages = {6664--6669},
doi = {10.21437/Interspeech.2026-2791},
issn = {2958-1796},
}
1 maintainer
Metadata
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