<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>1991</id>
    <completedYear>2024</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>358</pageFirst>
    <pageLast>367</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Association for Computational Linguistics</publisherName>
    <publisherPlace>Wien</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Linguistic and extralinguistic factors in automatic speech recognition of German atypical speech</title>
    <abstract language="eng">Automatic speech recognition (ASR) has been already used in speech and language therapy, including diagnostic tasks and practice exercises for people with aphasia (PWA). The lack of relevant data makes it difficult to evaluate the algorithms’ suitability for German-speaking PWA. For the current project, four open-source ASR models were selected based on their performance on other types of atypical speech, and the details of their evaluation are presented in this paper. The four selected models are generally robust to speakers’ gender and age. The one-word recognition yields better results for words of moderate length. Speech rate should be neither too slow nor too quick for lower error rates both in words and phrases, and the latter should be also of moderate length.</abstract>
    <parentTitle language="eng">Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024)</parentTitle>
    <identifier type="url">https://aclanthology.org/2024.konvens-main.36/</identifier>
    <identifier type="urn">urn:nbn:de:kobv:526-opus4-19915</identifier>
    <enrichment key="opus.import.date">2025-01-23T11:00:24+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">sword</enrichment>
    <enrichment key="SourceTitle">Eugenia Rykova and Mathias Walther. 2024. Linguistic and extralinguistic factors in automatic speech recognition of German atypical speech. In Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024), pages 358–367, Vienna, Austria. Association for Computational Linguistics.</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Eugenia Rykova</author>
    <author>Mathias Walther</author>
    <collection role="ddc" number="006">Spezielle Computerverfahren</collection>
    <collection role="ddc" number="616">Krankheiten</collection>
    <collection role="institutes" number="">Fachbereich Wirtschaft, Informatik, Recht</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="Import" number="import">Import</collection>
    <thesisPublisher>Technische Hochschule Wildau</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-th-wildau/files/1991/2024.konvens-main.36.pdf</file>
  </doc>
</export-example>
