Social and Behavioral Sciences Commons^™

Text-Speech Alignment: A Robin Hood Approach For Endangered Languages, Claire Bowern, Rikker Dockum, Sarah Babinski, Hunter Craft, Anelisa Fergus, Dolly Goldenberg

Yale Day of Data

Forced alignment automatically aligns audio recordings of spoken language with transcripts at the level of individual sounds, greatly reducing the time required to prepare data for linguistic analysis. However, existing algorithms are mostly trained on a few well-documented languages. We test the performance of three algorithms against manually aligned data on data from a highly endangered language. At least some tasks, unsupervised alignment (either based on English or trained from a small corpus) is sufficiently reliable for it to be used on legacy data for low-resource languages. Descriptive phonetic work on vowel inventories and prosody can be accurately captured by …