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Description
  • In the present text, we deal with the problem of classification of speech emotion. Problems of speech processing are addressed through the use of artificial neural networks (ANN). The results can be use for two research projects - for prosody modelling and for analysis of disordered speech. The first ANN topology discussed is the multilayer neural network (MLNN) with the BPG learning algorithm, while the supervised SOM (SSOM) are the second ANN topology. Our aim is to verify the various of knowledge from phonetics and ANN but also to try to classify speech signals which are described by musical theory. Finally, one solution is given for this problem which is supplemented with a proof.
  • In the present text, we deal with the problem of classification of speech emotion. Problems of speech processing are addressed through the use of artificial neural networks (ANN). The results can be use for two research projects - for prosody modelling and for analysis of disordered speech. The first ANN topology discussed is the multilayer neural network (MLNN) with the BPG learning algorithm, while the supervised SOM (SSOM) are the second ANN topology. Our aim is to verify the various of knowledge from phonetics and ANN but also to try to classify speech signals which are described by musical theory. Finally, one solution is given for this problem which is supplemented with a proof. (en)
Title
  • Emotional Speech Analysis using Artificial Neural Networks.
  • Emotional Speech Analysis using Artificial Neural Networks. (en)
skos:prefLabel
  • Emotional Speech Analysis using Artificial Neural Networks.
  • Emotional Speech Analysis using Artificial Neural Networks. (en)
skos:notation
  • RIV/68407700:21230/10:00174760!RIV11-GA0-21230___
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  • P(GA102/09/0989)
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  • 257023
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  • RIV/68407700:21230/10:00174760
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  • Emotions; speech; artificial neural networks; musical theory. (en)
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  • [0FE0B9087F61]
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  • Wisla
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  • Wroclaw
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  • Proceedings of the International Multiconference on Computer Science and Information Technology
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  • Tučková, Jana
  • Šramka, Martin
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http://linked.open.../riv/zahajeniAkce
issn
  • 1896-7094
number of pages
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  • Polska Akademia Nauk
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  • 978-83-60810-27-9
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  • 21230
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