Speech emotion recognition is an interesting and challenging speech technology, which can be applied to broad areas. In this paper, we propose to fuse the global statistical and segmental spectral features at the decision level for speech emotion recognition. Each emotional utterance is individually scored by two recognition systems, the global statistics-based and segmental spectrum-based syst...

Recently recognition of emotions became very important in the field of speech and/or speaker recognition. This paper is dedicated to experimental investigation of best acoustic features obtained for purpose of gender-dependent speaker recognition from emotional speech. Four feature sets LPC (Linear Prediction Coefficients), LPCC (Linear Prediction Cepstral Coefficients), MFCC (Melfrequency Ceps...

Artificial Intelligence (AI) based Speech Emotion Recognition (SER) has been widely used in the consumer field for control of smart home personal assistants, with many such devices on market. However, increase computational power, connectivity, and need to enable people live longer though use technology, then assistants that could detect human emotion will improve communication between a user a...

A number of recent studies have attempted classification of emotional speech using various methods. In this paper we compare the performance of two algorithms: a classification algorithm based on euclidean distances, and a classification algorithm based on the use of neural networks. Both perform the classification using an identical feature set, on a database of emotional speech which has been...

This paper describes and evaluates four different HSMM (hidden semi-Markov model) training methods for HMM-based synthesis of emotional speech. The first method, called emotion-dependent modelling, uses individual models trained for each emotion separately. In the second method, emotion adaptation modelling, at first a model is trained using neutral speech, and thereafter adaptation is performe...

from Anty Foundation and all the other researchers in VUB ETRO-DSSP for their valuable contribution and support throughout this project. Abstract The goal of this project is to produce affective speech that can convey natural vocal emotions in a non-existing and non-understandable language. The system uses a database with natural expressive speech samples from a professional speaker and a datab...

The ability for humans to understand and process the emotional content of speech is unsurpassed by simulated intelligent agents. Beyond the linguistic content of speech are the underlying prosodic features naturally understood by humans. The goal of emotional speech processing systems is to extract and classify human speech for these so called paralinguistic elements. Presented here is a proof-...

Emotional speech recognition is a multidisciplinary research area that has received increasing attention over the last few years. The present paper considers the application of restricted Boltzmann machines (RBM) and deep belief networks (DBN) to the difficult task of automatic Spanish emotional speech recognition. The principal motivation lies in the success reported in a growing body of work ...

Researches in speech synthesis and speech analysis are underpinned by the databases they used. The performance of an emotion classifier relies heavily on the qualities of the training and testing data. A good database can make researches in these fields achieving better results. Hearing-impaired people are poor in presenting their emotions in speech. We want develop a computer-assisted speech t...

setup of an emotion recognition or emotional speech recognition system is directly related to how emotion changes the speech features. in this research, the influence of emotion on the anger and happiness was evaluated and the results were compared with the neutral speech. so the pitch frequency and the first three formant frequencies were used. the experimental results showed that there are lo...