This paper analysis the feature of the time amplitude pitch and formant construction involved such four emotions as happiness anger surprise and sorrow. Through comparison with non-emotional speech signal, we sum up the distribution law of emotional feature including different emotional speech. Nine emotional features were extracted from emotional speech for recognizing emotion. We introduce th...

Due to the advance of speech technologies and their increasing usage in various applications, automatic recognition of emotions in speech represents one of the emerging fields in human-computer interaction. This paper deals with several topics related to automatic emotional speech recognition, most notably with the improvement of recognition accuracy by lowering the dimensionality of the featur...

We explore the construction of a system to classify the dominant emotion in spoken utterances, in a environment where resources such as labelled utterances are scarce. The research addresses two issues relevant to detecting emotion in speech: (a) compensating for the lack of resources and (b) finding features of speech which best characterise emotional expression in the cultural environment bei...

Processing emotional speech is an important issue for speech information science and there are many studies working on this issue. However, we still have no clear knowledge to answer what are the crucial acoustic features for emotional speech, except the fundamental frequency, and how human manipulate their speech organs to generate emotional speech. In this study, we investigate the acoustic f...

The present work studies the effect of emotional speech on a smarthome application. Specifically, we evaluate the recognition performance of the automatic speech recognition component of a smart-home dialogue system for various categories of emotional speech. The experimental results reveal that word recognition rate for emotional speech varies significantly across different emotion categories.

Perceived vocal features of emotional speech have rarely been investigated. In this contribution, a procedure allowing to collect reliable judgments on the perception of voice characteristics of emotional speech is presented. Relations between acoustic parameters and perceived features of speech are described. Some benefits and potential drawbacks of studying perceived vocal features in emotion...

Emotional speech recognition is the problem of discriminating speech samples by their emotional content. Our solution to this problem lies on three areas: signal processing, computational linguistics, and statistical learning. At signal processing and computational linguistics levels, identification and extraction of speech features is concerned; proposed in this work is a set of acoustic and l...

The paper analyzes the prosody features, which includes the intonation, speaking rate, intensity, based on classified emotional speech. As an important feature of voice quality, voice source are also deduced for analysis. With the analysis results above, the paper creates both a CART model and a weight decay neural network model to find acoustic importance towards the emotional speech classific...

This paper describes the modeling of various emotional expressions and speaking styles in synthetic speech using HMM-based speech synthesis. We show two methods for modeling speaking styles and emotional expressions. In the first method called style-dependent modeling, each speaking style and emotional expression is modeled individually. In the second one called style-mixed modeling, each speak...