Milana Bojanic

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Emotional speech recognition (ESR) from the aspect of human-machine interaction (HCI) is a prerequisite for the framework of interacting partners within the HCI. This paper addresses the application of neural network (NN) in ESR. The performance of NN is tested using three different feature sets which are basis for ESR: prosodic features, spectral features(More)
This paper reports on the application of the dimensional emotion model in automatic emotional speech recognition. Using the perceptron rule in combination with acoustic features, an approach to speech-based emotion recognition is introduced, which can classify the utterance with respect to the valence-arousal (V-A) dimensions of its emotional content. The(More)
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(More)
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