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Extension of HVS semantic parser by allowing left-right branching

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F08%3A00500817" target="_blank" >RIV/49777513:23520/08:00500817 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Extension of HVS semantic parser by allowing left-right branching

  • Original language description

    The hidden vector state (HVS) parser is a popular method for semantic parsing. It is used in the language understanding module of the statistical based spoken dialog system. This paper presents an extension of the HVS semantic parser. It enables the parser to generate broader class of semantic trees. This modication can be used to improve the performance of the parser by generating not only the right-branching trees (like original HVS parser) but also limited left-branching trees and their combinations.The extension retains simplicity and properties of the original HVS parser. We tested the method on Czech human-human train timetable corpus. The modied HVS parser yields statistically signicant improvement. The accuracy of the system increased from 50.4% to 58.3% absolutely.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

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

    2008

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2008 IEEE International Conference on Acoustics, Speech, and Signal Processing

  • ISBN

    978-1-4244-1483-3

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

  • Publisher name

    IEEE

  • Place of publication

    New York

  • Event location

    Las Vegas, Nevada, U.S.A.

  • Event date

    Apr 4, 2008

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000257456703232