About: Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	The present paper proposes a new speaker-independent approach to the classification of emotional vocal expressions by using the COST 2102 Italian database of emotional speech. The audio records extracted from video clips of Italian movies possess a certain degree of spontaneity and are either noisy or slightly degraded by an interruption making the collected stimuli more realistic in comparison with available emotional databases containing utterances recorded under studio conditions. The audio stimuli represent 6 basic emotional states: happiness, sarcasm/irony, fear, anger, surprise, and sadness. For these more realistic conditions, and using a speaker independent approach, the proposed system is able to classify the emotions under examination with 60.7% accuracy by using a hierarchical structure consisting of a Perceptron and fifteen Gaussian Mixture Models (GMM) trained to distinguish within each pair (couple) of emotions under examination. The best features in terms of high discriminative power we The present paper proposes a new speaker-independent approach to the classification of emotional vocal expressions by using the COST 2102 Italian database of emotional speech. The audio records extracted from video clips of Italian movies possess a certain degree of spontaneity and are either noisy or slightly degraded by an interruption making the collected stimuli more realistic in comparison with available emotional databases containing utterances recorded under studio conditions. The audio stimuli represent 6 basic emotional states: happiness, sarcasm/irony, fear, anger, surprise, and sadness. For these more realistic conditions, and using a speaker independent approach, the proposed system is able to classify the emotions under examination with 60.7% accuracy by using a hierarchical structure consisting of a Perceptron and fifteen Gaussian Mixture Models (GMM) trained to distinguish within each pair (couple) of emotions under examination. The best features in terms of high discriminative power we (en)
Title	Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech (en)
skos:prefLabel	Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech (en)
skos:notation	RIV/00216305:26220/09:PU84458!RIV11-MSM-26220___
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(OC08057), Z(MSM0021630513)
http://linked.open...iv/cisloPeriodika	5967
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Atassi, Hicham Smékal, Zdeněk
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	313112
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/09:PU84458
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	emotion recognition, speech, Italian database, spectral features, high level features. (en)
http://linked.open.../riv/klicoveSlovo	spectral features speech emotion recognition Italian database high level features.
http://linked.open...odStatuVydavatele	DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV	[A9DF71A35AF2]
http://linked.open...i/riv/nazevZdroje	Lecture Notes in Computer Science (IF 0,513)
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...vavai/riv/projekt	Analysis and Enhancement of Speech and Image Signals form Noise for Cross-Modal Analysis of Verbal and Non-verbal Communication
http://linked.open...UplatneniVysledku	2009
http://linked.open...v/svazekPeriodika	2009
http://linked.open...iv/tvurceVysledku	Atassi, Hicham Esposito, Anna Smékal, Zdeněk Hussain, Amir Riviello, Maria Teresa
http://linked.open...n/vavai/riv/zamer	Advanced Electronic Communication Systems and Technologies (ELCOM)
issn	0302-9743
number of pages	14 (xsd:int)
http://localhost/t...ganizacniJednotka	26220
is http://linked.open...avai/riv/vysledek of	Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech Emotional Vocal Expressions Recognition using the COST 2102 Italian Database of Emotional Speech

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software