Comparison of syllabification algorithms and training strategies for robust word count estimation across different languages and recording conditions

Okko Räsänen, Shreyas Seshadri, Marisa Casillas

    Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

    5 Sitaatiot (Scopus)
    177 Lataukset (Pure)

    Abstrakti

    Word count estimation (WCE) from audio recordings has a number of applications, including quantifying the amount of speech that language-learning infants hear in their natural environments, as captured by daylong recordings made with devices worn by infants. To be applicable in a wide range of scenarios and also low-resource domains, WCE tools should be extremely robust against varying signal conditions and require minimal access to labeled training data in the target domain. For this purpose, earlier work has used automatic syllabification of speech, followed by a least-squares-mapping of syllables to word counts. This paper compares a number of previously proposed syllabifiers in the WCE task, including a supervised bi-directional long short-term memory (BLSTM) network that is trained on a language for which high quality syllable annotations are available (a “high resource language”), and reports how the alternative methods compare on different languages and signal conditions. We also explore additive noise and varying-channel data augmentation strategies for BLSTM training, and show how they improve performance in both matching and mismatching languages. Intriguingly, we also find that even though the BLSTM works on languages beyond its training data, the unsupervised algorithms can still outperform it in challenging signal conditions on novel languages.

    AlkuperäiskieliEnglanti
    OtsikkoProceedings of Interspeech
    KustantajaInternational Speech Communication Association
    Sivut1200-1204
    Sivumäärä5
    Vuosikerta2018-September
    DOI - pysyväislinkit
    TilaJulkaistu - 1 tammik. 2018
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
    TapahtumaInterspeech - Hyderabad International Convention Centre, Hyderabad, Intia
    Kesto: 2 syysk. 20186 syysk. 2018
    http://interspeech2018.org/

    Julkaisusarja

    NimiProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
    KustantajaInternational Speech Communication Association
    ISSN (painettu)2308-457X

    Conference

    ConferenceInterspeech
    Maa/AlueIntia
    KaupunkiHyderabad
    Ajanjakso02/09/201806/09/2018
    www-osoite

    Sormenjälki

    Sukella tutkimusaiheisiin 'Comparison of syllabification algorithms and training strategies for robust word count estimation across different languages and recording conditions'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

    Siteeraa tätä