This paper presents results from a study examining emotional speech using acoustic features and their use in automatic machine learning classification. In addition, we propose a classification scheme for the labeling of emotions on continuous scales. Our findings support those of previous research as well as indicate possible future directions utilizing spectral tilt and pitch contour to distinguish emotions in the valence dimension
Speech is a direct and rich way of transmitting information and emotions from one point to another. ...
Work on facial expressions of emotions (Calder, Burton, Miller, Young, & Akamatsu, 2001) and emotion...
Work on facial expressions of emotions (Calder, Burton, Miller, Young, & Akamatsu, 2001) and emotion...
In this thesis, we describe extensive experiments on the classification of emotions from speech usin...
In recent years, the interaction between humans and machines has become an issue of concern. This pa...
Creating machines with the ability to reason, perceive, learn and make decisions based on a human li...
This paper reports on the comparison between various acoustic feature sets and classification algori...
We developed acoustic and lexical classifiers, based on a boosting algorithm, to assess the separabi...
In this paper we present current results in emotion classi-cation based on features extracted from t...
In this paper, we consider both speaker dependent and listener dependent aspects in the assessment o...
Machine-based emotional intelligence is a requirement for natural interaction between humans and com...
Emotion recognition from Audio signal Recognition is a recent research topic in the Human Computer I...
Automatic affect prediction systems usually assume its underlying affect representation scheme (ARS)...
This chapter presents a comparative study of speech emotion recognition (SER) systems. Theoretical d...
In this study, we investigate acoustic properties of speech associ-ated with four different emotions...
Speech is a direct and rich way of transmitting information and emotions from one point to another. ...
Work on facial expressions of emotions (Calder, Burton, Miller, Young, & Akamatsu, 2001) and emotion...
Work on facial expressions of emotions (Calder, Burton, Miller, Young, & Akamatsu, 2001) and emotion...
In this thesis, we describe extensive experiments on the classification of emotions from speech usin...
In recent years, the interaction between humans and machines has become an issue of concern. This pa...
Creating machines with the ability to reason, perceive, learn and make decisions based on a human li...
This paper reports on the comparison between various acoustic feature sets and classification algori...
We developed acoustic and lexical classifiers, based on a boosting algorithm, to assess the separabi...
In this paper we present current results in emotion classi-cation based on features extracted from t...
In this paper, we consider both speaker dependent and listener dependent aspects in the assessment o...
Machine-based emotional intelligence is a requirement for natural interaction between humans and com...
Emotion recognition from Audio signal Recognition is a recent research topic in the Human Computer I...
Automatic affect prediction systems usually assume its underlying affect representation scheme (ARS)...
This chapter presents a comparative study of speech emotion recognition (SER) systems. Theoretical d...
In this study, we investigate acoustic properties of speech associ-ated with four different emotions...
Speech is a direct and rich way of transmitting information and emotions from one point to another. ...
Work on facial expressions of emotions (Calder, Burton, Miller, Young, & Akamatsu, 2001) and emotion...
Work on facial expressions of emotions (Calder, Burton, Miller, Young, & Akamatsu, 2001) and emotion...