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
—