In a database of emotional speech, dimensional descriptions of emotional states have been correlated with acoustic variables. Many stable correlations have been found. The predictions made by linear regression widely agree with the literature. The numerical form of the description and the choice of acoustic variables studied are particularly well suited for future implementation in a speech syn...

This paper describes an emotional speech synthesis system based on HMMs and related modeling techniques. For concatenative speech synthesis, we require all of the concatenation units that will be used to be recorded beforehand and made available at synthesis time. To adopt this approach for synthesizing the wide variety of human emotions possible in speech, implies that this process should be r...

In this paper, a large Finnish emotional speech database is introduced. The database contains simulated emotional speech, reflecting some of the affective states commonly known as basic emotions. The database has been analyzed instrumentally in terms of some 40 acoustic/prosodic parameters, and is currently being annotated in terms of a number of linguistically relevant contrasts. The annotatio...

A key element in affective computing is to have large corpora of genuine emotional samples collected during natural conversations. Recording natural interactions through telephone is an appealing approach to build emotional databases. However, collecting real conversational data with expressive reactions is a challenging task, especially if the recordings are to be shared with the community (e....

Automatic emotion recognition in speech is a research area with a wide range of applications in human interactions. The basic mathematical tool used for emotion recognition is Pattern recognition which involves three operations, namely, pre-processing, feature extraction and classification. This paper introduces a procedure for emotion recognition using Hidden Markov Models (HMM), which is used...

Recently, increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. This paper is a survey of speech emotion classification addressing three important aspects of the design of a speech emotion recognition system. The first one is the choice of suitable featur...

This paper describes the evaluation process of an emotional speech database recorded for standard Basque, in order to determine its adequacy for the analysis of emotional models and its use in speech synthesis. The corpus consists of seven hundred semantically neutral sentences that were recorded for the Big Six emotions and neutral style, by two professional actors. The test results show that ...

language and emotion are two related systems in use, in that one system (emotions) impacts the performance of the other (language). both of them share their functionality in communication. since the nature of foreign language classrooms is ideally interactional, emotional intelligence (ei) gains importance. the aim of this study was to find out whether one's total emotional quotient and its com...

The goal of this paper is to assess the effect of emotional state of a speaker when text-independent speaker identification is performed. Mel-frequency cepstral coefficients are the features of the speech signal used for speaker recognition. For training the speaker models and testing the system, Support Vector Machines are employed. Berlin emotional speech database, which contains 10 different...

We propose a simple method for modifying emotional speech sounds. The method aims at real-time implementation of an emotional expression transformation system based on STRAIGHT. We developed a mapping function of spectra, fundamental frequencies (F0), and vowel durations from the statistical analysis of 1500 expressive speech sounds in an emotional speech database. The spectral mapping paramete...