Recursive forced alignment: A test on a minority language

Simon Gonzalez, Catherine Travis, James Grama, Danielle Barth, Sunkulp Ananthanarayan

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    We compare recursive and linear approaches to force-aligned data from Matukar Panau, an endangered language of Papua New Guinea. Data were force aligned with the train/align procedure in the Montreal Forced Aligner. Using manual alignments produced by a trained phonetician as a benchmark, the recursive approach was found to outperform the linear approach. The recursive approach produced alignments that overlapped more with those made by human coders, and resulted in fewer fluctuations in both Overlap Rate and Error Rate. We conclude that a recursive approach enhances the quality of automated alignment of languages lacking a pre-existing acoustic model.
    Original languageEnglish
    Title of host publicationProceedings of the 17th Australasian International Conference on Speech Science and Technology
    EditorsJ Epps, J Wolfe, J Smith & C Jones
    Place of PublicationAustralia
    PublisherThe Australasian Speech Science and Technology Association, Inc.
    Pages145-148
    EditionPeer reviewed
    ISBN (Print)2207-1296
    Publication statusPublished - 2018
    Event17th Australasian International Conference on Speech Science and Technology - Sydney, Australia, Australia
    Duration: 1 Jan 2018 → …

    Conference

    Conference17th Australasian International Conference on Speech Science and Technology
    Country/TerritoryAustralia
    Period1/01/18 → …
    OtherDecember 4-7 2018

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