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This paper deals with automatic dialogue act recognition. Dialogue acts (DAs) are utterance-level labels that represent different states of a dialogue, such as questions, statements, hesitations, etc. Information about actual DA can be seen as the first level of dialogue understanding. The main goal of this paper is to compare our dialogue act recognition(More)
This paper deals with automatic dialog acts (Das) recognition in Czech based on sentence structure. We consider the following DAs: statements, orders, yes/no questions and other questions. In our previous works, we have proposed, implemented and evaluated new approaches to automatic DAs recognition based on sentence structure and prosody. The word sequences(More)
This article tries to compare the performance of neural network and Gaussian mixture acoustic models (GMMs). We argue that using a multi layer perceptron as an emission probability estimator in hidden Markov model based automatic speech recognition can lead to better results than when the more traditional Gaussian mixtures are applied. We present a solution(More)
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