Abstract
Speech emotion recognition (SER) poses one of the major challenges in human-machine interaction. We propose a new algorithm, the Voiced Segment Selection (VSS) algorithm, which can produce an accurate segmentation of speech signals. The VSS algorithm deals with the voiced signal segment as the texture image processing feature which is different from the traditional method. It uses the Log-Gabor filters to extract the voiced and unvoiced features from spectrogram to make the classification. The finding shows that the VSS method is a more accurate algorithm for voiced segment detection. Therefore, it has potential to improve performance of emotion recognition from speech.
Original language | English |
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Title of host publication | ECAI 2016 - 22nd European Conference on Artificial Intelligence |
Editors | Gal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum, Frank van Harmelen |
Publisher | IOS Press |
Pages | 1682-1683 |
Number of pages | 2 |
ISBN (Electronic) | 978-1-61499-672-9 |
ISBN (Print) | 978-1-61499-671-2 |
DOIs | |
Publication status | Published - 2016 |
Event | ECAI 2016: 22nd European Conference on Artificial Intelligence 2016 - World Forum, The Hague, Netherlands Duration: 29 Aug 2016 → 2 Sept 2016 Conference number: 22 http://www.ecai2016.org/ |
Publication series
Name | Frontiers in Artificial Intelligence and Applications |
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Volume | 285 |
Conference
Conference | ECAI 2016 |
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Abbreviated title | ECAI 2016 |
Country/Territory | Netherlands |
City | The Hague |
Period | 29/08/16 → 2/09/16 |
Other | Including Prestigious Applications of Artificial Intelligence, PAIS 2016 |
Internet address |