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Hauptverfasser: Tosolini, Alessio, Bowern, Claire
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2504.07315
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author Tosolini, Alessio
Bowern, Claire
author_facet Tosolini, Alessio
Bowern, Claire
contents We compare the outcomes of multilingual and crosslingual training for related and unrelated Australian languages with similar phonological inventories. We use the Montreal Forced Aligner to train acoustic models from scratch and adapt a large English model, evaluating results against seen data, unseen data (seen language), and unseen data and language. Results indicate benefits of adapting the English baseline model for previously unseen languages.
format Preprint
id arxiv_https___arxiv_org_abs_2504_07315
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multilingual MFA: Forced Alignment on Low-Resource Related Languages
Tosolini, Alessio
Bowern, Claire
Computation and Language
We compare the outcomes of multilingual and crosslingual training for related and unrelated Australian languages with similar phonological inventories. We use the Montreal Forced Aligner to train acoustic models from scratch and adapt a large English model, evaluating results against seen data, unseen data (seen language), and unseen data and language. Results indicate benefits of adapting the English baseline model for previously unseen languages.
title Multilingual MFA: Forced Alignment on Low-Resource Related Languages
topic Computation and Language
url https://arxiv.org/abs/2504.07315