Speech Emotions Recognition Using 2-D Neural Classifier

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86086876" target="_blank" >RIV/61989100:27240/13:86086876 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/13:86086876

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Speech Emotions Recognition Using 2-D Neural Classifier

Popis výsledku v původním jazyce

This article deals with a speech emotion recognition system. We discuss the usage of a neural network as the final classifier for human speech emotional state. We carried our research on a database of records of both genders and various emotional states.In the preprocessing and speech processing phase, we focused our intent on parameters dependent on the emotional state. The output of this work is a system for classifying the emotional state of a man's voice, which is based on a neural network classifier. For output-stage classifier was used self-organizing feature map, which is specific type of artificial neural nets. The number of input parameters must be limited for hardware and time consuming computation of neurons positions. Therefore we discussthe accuracy of the classifier whose input is the fundamental frequency calculated by different methods

Název v anglickém jazyce

Speech Emotions Recognition Using 2-D Neural Classifier

Popis výsledku anglicky

This article deals with a speech emotion recognition system. We discuss the usage of a neural network as the final classifier for human speech emotional state. We carried our research on a database of records of both genders and various emotional states.In the preprocessing and speech processing phase, we focused our intent on parameters dependent on the emotional state. The output of this work is a system for classifying the emotional state of a man's voice, which is based on a neural network classifier. For output-stage classifier was used self-organizing feature map, which is specific type of artificial neural nets. The number of input parameters must be limited for hardware and time consuming computation of neurons positions. Therefore we discussthe accuracy of the classifier whose input is the fundamental frequency calculated by different methods

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

Advances in Intelligent Systems and Computing. Volume 239

ISSN

2194-5357

e-ISSN

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Svazek periodika

210

Číslo periodika v rámci svazku

2013

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

11

Strana od-do

221-231

Kód UT WoS článku

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EID výsledku v databázi Scopus

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