Automatic speech recognition can fail to a certain extent when confronted with emotionally distorted speech. Great efforts have been spent so far to cope with noise conditions or speaker’s characteristics. Yet, adaptation to the emotional condition of the speaker could help to further improve the overall performance. In this respect we aim at a robust and reliable recognition of the speaker’s e...

In the present work we address the problem of phone duration modeling for the needs of emotional speech synthesis. Specifically, relying on ten well known machine learning techniques, we investigate the practical usefulness of two feature selection techniques, namely the Relief and the Correlation-based Feature Selection (CFS) algorithms, for improving the accuracy of phone duration modeling. T...

Many acoustic features convey emotion similarly in speech and music. Researchers have established that acoustic features such as pitch height, tempo, and intensity carry important emotional information in both domains. In this investigation, we examined the emotional significance of melodic and rhythmic contrasts between successive syllables or tones in speech and music, referred to as Melodic ...

Emotional expression is a key requirement for intelligent virtual agents. In order for an agent to produce dynamic spoken content speech synthesis is required. However, despite substantial work with prerecorded prompts, very little work has explored the combined effect of high quality emotional speech synthesis and facial expression. In this paper we offer a baseline evaluation of the naturalne...

Communicative goals are simultaneously expressed through gestures and speech to convey messages enriched with valuable verbal and non-verbal clues. This paper analyzes and quantifies how linguistic and affective goals are reflected in facial expressions. Using a database recorded from an actress with markers attached to her face, the facial features during emotional speech were compared with th...

Synthesizing emotional speech by means of conversion from neutral speech allows us to generate emotional speech from many existing Text-to-Speech (TTS) systems. How much of the target emotion can be portrayed by the generated speech is largely dependent on the emotion data used to train the mapping function for voice transformation. In this paper, we introduce a method to pre-process the emotio...

The investigations of emotional speech identification can be divided into two main parts, features and classifiers. In this paper, how to extract an effective speech feature set for the emotional speech identification is addressed. In our speech feature set, we use not only statistical analysis of frame-based acoustical features, but also the approximated speech feature contours, which are obta...

The paper presents an emotional speech recognition system with the analysis of manifolds of speech. Working with large volumes of high-dimensional acoustic features, the researchers confront the problem of dimensionality reduction. Unlike classical techniques, such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), a new approach, named Enhanced Lipschitz Embedding (E...

In this paper, we proposed a new feature extraction method for emotion recognition based on the knowledge of the emotion production mechanism in physiology. It was reported by physiacoustist that emotional speech is differently encoded from the normal speech in terms of articulation organs and that emotion information in speech is concentrated in different frequencies caused by the different mo...

Cultural differences have been one of the many factors that can cause failures in speech emotion analysis. If this cultural parameter could be regarded as noise artifacts in detecting emotion in speech, we could then extract pure emotion speech signal from the raw emotional speech. In this paper we use the amplitude spectral subtraction (ASS) method to profile the emotion from raw emotional spe...