Print Email Facebook Twitter Speech Emotion Recognition Using Voiced Segment Selection Algorithm Title Speech Emotion Recognition Using Voiced Segment Selection Algorithm Author Gu, Yu (Tilburg University) Postma, Eric (Tilburg University) Lin, H.X. (TU Delft Mathematical Physics) van den Herik, Jaap (Universiteit Leiden) Contributor Kaminka, Gal A. (editor) Fox, Maria (editor) Bouquet, Paolo (editor) Hüllermeier, Eyke (editor) Dignum, Virginia (editor) Dignum, Frank (editor) van Harmelen, Frank (editor) Date 2016 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. To reference this document use: http://resolver.tudelft.nl/uuid:c3d8ee74-8f9b-4a46-83dc-855f66749f5a DOI https://doi.org/10.3233/978-1-61499-672-9-1682 Publisher IOS Press ISBN 978-1-61499-671-2 Source ECAI 2016 - 22nd European Conference on Artificial Intelligence Event ECAI 2016, 2016-08-29 → 2016-09-02, World Forum, The Hague, Netherlands Series Frontiers in Artificial Intelligence and Applications, 285 Part of collection Institutional Repository Document type conference paper Rights © 2016 Yu Gu, Eric Postma, H.X. Lin, Jaap van den Herik Files PDF 10639597.pdf 222.25 KB Close viewer /islandora/object/uuid:c3d8ee74-8f9b-4a46-83dc-855f66749f5a/datastream/OBJ/view