An Automatic Emotion Recognizer using MFCCs and Hidden Markov Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU115941" target="_blank" >RIV/00216305:26220/15:PU115941 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
An Automatic Emotion Recognizer using MFCCs and Hidden Markov Models
Original language description
In this paper, the proficiency of continuous Hidden Markov Models to recognize emotions from speech signals has been investigated. Unlike the existing work which considers prosodic features for automatic emotion recognition, this work proposes the effectiveness of the phonetic features of speech particularly, Mel-Frequency Cepstral Coefficients which improves the accuracy with reduced feature set. The continuous speech emotional utterances used in this work have been taken from the SAVEE emotional corpus. The Hidden Markov Model Toolkit (HTK) version 3.4.1 was utilized for extraction of the acoustic features as well as generation of the models. Optimizing the acoustic and pre-processing parameters along with the number of states and transition probabilities of the Markov Models, the trials give us an average accuracy of 78% and highest accuracy of 91.25% for four emotions sadness, surprise, fear and disgust.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JA - Electronics and optoelectronics
OECD FORD branch
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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)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2015 7th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
ISBN
978-1-4673-9282-2
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
320-324
Publisher name
Neuveden
Place of publication
Brno, Czech Republic
Event location
Brno
Event date
Oct 6, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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