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Genre and emotion have been applied to content-based music retrieval and organization; however, the intrinsic correlation between them has not been explored. In this paper we present a statistical association analysis to examine such intrinsic correlation and propose a two-layer scheme that exploits the correlation for emotion classification. Significant improvement of classification accuracy over...
In this paper, automatic identification of emotional states from human speech is addressed. While several papers have been published in the literature on speech emotion recognition, the features used are taken or modified from those used for speech recognition purposes. However, not all features used for speech recognition are of equal importance for emotion recognition. This paper addresses this...
The annotation of hundreds of thousands of utterances for the training of statistical utterance classifiers requires a careful quality assurance procedure to make the data consistent and reliable. In this paper, we present five methods to analyze different aspects of annotated data to ensure their Completeness, Consistency, Correlation, Congruence and to avoid Confusion-collectively referred to as...
The neural networks find many applications today in different kinds of real-time working systems. To obtain short execution times and high recognition accuracy in real-time decision-making systems becomes a question of first importance. Therefore, the requirements to the recognition stage in such systems in reference to reduce the reaction time grow up. In the proposed research a new method for optimization...
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