Theodoros Iliou

Learn More
Speaker emotion recognition is achieved through processing methods that include isolation of the speech signal and extraction of selected features for the final classification. In terms of acoustics, speech processing techniques offer extremely valuable paralinguistic information derived mainly from prosodic and spectral features. In some cases, the process(More)
In this paper, we present a comparative analysisof three classifiers for speech signal emotion recognition.Recognition was performed on emotional Berlin Database.This work focuses on speaker and utterance (phrase)dependent and independent framework. One hundred thirtythree (133) sound/speech features were extracted from Pitch,Mel Frequency Cepstral(More)
This paper presents an emotion recognition framework based on sound processing could significantly improve human computer interaction. One hundred thirty three (133) speech features obtained from sound processing of acting speech were tested in order to create a feature set sufficient to discriminate between seven emotions. Following statistical analysis in(More)
In the present paper a comparison of two classifiers for speech signal emotion recognition is presented. Recognition was performed on emotional Berlin Database. Within this work we concentrate on the evaluation of a speaker-dependent and speaker independent emotion recognition classification. One hundred thirty three (133) speech features obtained from(More)
Data preprocessing describes any type of processing methods performed on raw data to prepare it for another processing procedure. Commonly used as a preliminary data mining practice, data preprocessing methods transforms the data into a format that will be more easily and effectively processed for the classification algorithms. In this paper, a novel data(More)