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Unsupervised Word Segmentation from Speech with Attention

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU136058" target="_blank" >RIV/00216305:26230/18:PU136058 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.isca-speech.org/archive/Interspeech_2018/pdfs/1308.pdf" target="_blank" >https://www.isca-speech.org/archive/Interspeech_2018/pdfs/1308.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.21437/Interspeech.2018-1308" target="_blank" >10.21437/Interspeech.2018-1308</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Unsupervised Word Segmentation from Speech with Attention

  • Original language description

    We present a first attempt to perform attentional word segmentation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource, unwritten language (UL). Our methodology assumes a pairing between recordings in the UL with translations in a well-resourced language. It uses Acoustic Unit Discovery (AUD) to convert speech into a sequence of pseudo-phones that is segmented using neural soft-alignments produced by a neural machine translation model. Evaluation uses an actual Bantu UL, Mboshi; comparisons to monolingual and bilingual baselines illustrate the potential of attentional word segmentation for language documentation.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceeding of Interspeech 2018

  • ISBN

  • ISSN

    1990-9772

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    2678-2682

  • Publisher name

    International Speech Communication Association

  • Place of publication

    Hyderabad

  • Event location

    Hyderabad, India

  • Event date

    Sep 2, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000465363900561