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Intonation Based Sentence Modality Classifier for Czech Using Artificial Neural Network

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00183476" target="_blank" >RIV/68407700:21230/11:00183476 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Intonation Based Sentence Modality Classifier for Czech Using Artificial Neural Network

  • Original language description

    This paper presents an idea and first results of sentence modality classifier for Czech based purely on intonational information. This is in contrast with other studies which usually use more features (including lexical features) for this type of classification. As the sentence melody (intonation) is the most important feature, all the experiments were done on an annotated sample of Czech audiobooks library recorded by Czech leading actors. A non-linear model implemented by artificial neural network (ANN) was chosen for the classification. Two types of ANN are considered in this work in terms of temporal pattern classifications - classical multi-layer perceptron (MLP) network and Elman's network, results for MLP are presented. Pre-processing of temporal intonational patterns for use as ANN inputs is discussed. Results show that questions are very often misclassified as statements and exclamation marks are not detectable in current data set.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JA - Electronics and optoelectronics

  • 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

    2011

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Advances in Nonlinear Speech Processing

  • ISBN

    978-3-642-25019-4

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    162-169

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Las Palmas de Gran Canaria

  • Event date

    Nov 7, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article