BACKGROUND The study of emotional speech perception and emotional prosody necessitates stimuli with reliable affective norms. However, ratings may be affected by the participants' current emotional state as increased anxiety and depression have been shown to yield altered neural responding to emotional stimuli. Therefore, the present study had two aims, first to provide a database of emotional ...

One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...

The article describes a database of emotional speech. Ten actors (5 female and 5 male) simulated the emotions, producing 10 German utterances (5 short and 5 longer sentences) which could be used in everyday communication and are interpretable in all applied emotions. The recordings were taken in an anechoic chamber with high-quality recording equipment. In addition to the sound electro-glottogr...

This article describes the first emotional corpus, named EMOVO, applicable to Italian language,. It is a database built from the voices of up to 6 actors who played 14 sentences simulating 6 emotional states (disgust, fear, anger, joy, surprise, sadness) plus the neutral state. These emotions are the well-known Big Six found in most of the literature related to emotional speech. The recordings ...

We propose a new approach to synthesizing emotional speech by a corpus-based concatenative speech synthesis system (ATR CHATR) using speech corpora of emotional speech. In this study, neither emotional-dependent prosody prediction nor signal processing per se is performed for emotional speech. Instead, a large speech corpus is created per emotion to synthesize speech with the appropriate emotio...

This work aims at intensifying text-independent speaker identification performance in real application situations such as noisy and emotional talking conditions. is achieved by incorporating two different modules: a Computational Auditory Scene Analysis (CASA) based pre-processing module for noise reduction “cascaded Gaussian Mixture Model – Convolutional Neural Network (GMM-CNN) classifier ide...

The MediaTeam Emotional Speech Corpus is currently the largest database of emotional speech for colloquial modern Finnish, containing simulated emotional content. The specific aim of the research is to investigate in detail the phonetic and phonological/linguistic correlates of basic or primary emotions in spoken Finnish, to develop statistical classification methods of emotional speech signals...

Modern Speech synthesisers have achieved a high degree of intelligibility, but can not be regarded as natural-sounding devices. In order to decrease the monotony of synthetic speech, the implementation of emotional effects is now being progressively considered. This paper presents a through study of emotional speech in Spanish, and its application to TTS, presenting a prototype system that simu...

A Greek Emotional Speech Database has been recorded and analyzed. The scope of this work is to study through this database the prosodical phenomena as a function of each emotional state and the application to a text to speech synthesis system. Our database contains recordings of a female professional actress. We used an actress for this task because in order to faithfully simulate a number of e...