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Hybrid Dialog State Tracker with ASR Features

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372185" target="_blank" >RIV/00216208:11320/17:10372185 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Hybrid Dialog State Tracker with ASR Features

  • Original language description

    This paper presents a hybrid dialog state tracker enhanced by trainable Spoken Language Understanding (SLU) for slot-filling dialog systems. Our architecture is inspired by previously proposed neural-network-based belief-tracking systems. In addition, we extended some parts of our modular architecture with differentiable rules to allow end-to-end training. We hypothesize that these rules allow our tracker to generalize better than pure machine-learning based systems. For evaluation, we used the Dialog State Tracking Challenge (DSTC) 2 dataset - a popular belief tracking testbed with dialogs from restaurant information system. To our knowledge, our hybrid tracker sets a new state-of-the-art result in three out of four categories within the DSTC2.

  • 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

    2017

  • 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 the 15th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers

  • ISBN

    978-1-5108-3860-4

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    6

  • Pages from-to

    205-210

  • Publisher name

    Association for Computational Linguistics

  • Place of publication

    Stroudsburg, PA, USA

  • Event location

    Valencia, Spain

  • Event date

    Apr 3, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article