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Sequence Summarizing Neural Networks for Spoken Language Recognition

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU121675" target="_blank" >RIV/00216305:26230/16:PU121675 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.researchgate.net/publication/307889421_Sequence_Summarizing_Neural_Networks_for_Spoken_Language_Recognition" target="_blank" >https://www.researchgate.net/publication/307889421_Sequence_Summarizing_Neural_Networks_for_Spoken_Language_Recognition</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.21437/Interspeech.2016-764" target="_blank" >10.21437/Interspeech.2016-764</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Sequence Summarizing Neural Networks for Spoken Language Recognition

  • Original language description

    This paper explores the use of Sequence Summarizing Neural Networks (SSNNs) as a variant of deep neural networks (DNNs) for classifying sequences. In this work, it is applied to the task of spoken language recognition. Unlike other classification tasks in speech processing where the DNN needs to produce a per-frame output, language is considered constant during an utterance. We introduce a summarization component into the DNN structure producing one set of language posteriors per utterance. The training of the DNN is performed by an appropriately modified gradient-descent algorithm. In our initial experiments, the SSNN results are compared to a single state-of-the-art i-vector based baseline system with a similar complexity (i.e. no system fusion, etc.). For some conditions, SSNNs is able to provide performance comparable to the baseline system. Relative improvement up to 30% is obtained with the score level fusion of the baseline and the SSNN systems.

  • 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

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of Interspeech 2016

  • ISBN

    978-1-5108-3313-5

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    3285-3289

  • Publisher name

    International Speech Communication Association

  • Place of publication

    San Francisco

  • Event location

    San Francisco

  • Event date

    Sep 8, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000409394402038