Extraction of Novel Features Based on Histograms of MFCCs Used in Emotion Classification from Generated Original Speech Dataset

Extraction of Novel Features Based on Histograms of MFCCs Used in Emotion Classification from Generated Original Speech Dataset

This paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from speech signals, and the other – our new multi-lingual and multi-personal speech d...

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Bibliographic Details
Main Authors: Muhammet Pakyurek, Mahir Atmis, Selman Kulac, Umut Uludag
Format: Article
Language:English
Published: Kaunas University of Technology 2020-02-01
Series:Elektronika ir Elektrotechnika
Subjects:
emotion classification
mfcc
svm
speech signal
Online Access:http://eejournal.ktu.lt/index.php/elt/article/view/25309

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