Improved Frame Level Features and SVM Supervectors Approach for the Recogniton of Emotional States from Speech: Application to categorical and dimensional states

Autor:	Trabelsi, Imen, Ayed, Dorra Ben, Ellouze, Noureddine
Rok vydání:	2014
Předmět:	Computer Science - Computation and Language Computer Science - Learning
Zdroj:	I.J. Image, Graphics and Signal Processing, 2013, 9, 8-13
Druh dokumentu:	Working Paper
DOI:	10.5815/ijigsp.2013.09.02
Popis:	The purpose of speech emotion recognition system is to classify speakers utterances into different emotional states such as disgust, boredom, sadness, neutral and happiness. Speech features that are commonly used in speech emotion recognition rely on global utterance level prosodic features. In our work, we evaluate the impact of frame level feature extraction. The speech samples are from Berlin emotional database and the features extracted from these utterances are energy, different variant of mel frequency cepstrum coefficients, velocity and acceleration features.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1406.6101 Zobrazit plný text záznamu View this record from Arxiv