Arată înregistrarea sumară a articolului
A Novel Feature Extraction Method for Isolated Word Recognition Based on Nested Temporal Averaging
dc.contributor.author | Dogaru, Radu | |
dc.contributor.author | Costache, Gabriel Nicolae | |
dc.contributor.author | Dumitru, Octavian | |
dc.contributor.author | Gavat, Inge | |
dc.date.accessioned | 2016-01-13T10:51:13Z | |
dc.date.available | 2016-01-13T10:51:13Z | |
dc.date.issued | 2006 | |
dc.identifier.uri | http://10.11.10.50/xmlui/handle/123456789/3867 | |
dc.description | The Annals of "Dunarea de Jos" University of Galati | en_US |
dc.description.abstract | A novel preprocessing method is proposed. It has a reduced complexity and therefore is aimed to be used in low power, VLSI implemented, speech recognizers. Our algorithm extracts a feature vector made from up to 3 feature vectors, each coming from a particular variable length speech sequence. The sequences are nested one into each other while their length is divided by 2 for each nesting operation. Each feature vector is computed as an average, min and max of all 13-dimensional Mel-cepstral coefficients obtained within a sound sequence. On a sound database with 10 speakers speaking 7 different words the classification performance was found to be close and even better than the one obtained using traditional methods (HMMs) | en_US |
dc.language.iso | en | en_US |
dc.publisher | "Dunarea de Jos" University of Galati | en_US |
dc.subject | Speech recognition | en_US |
dc.subject | Support Vector | en_US |
dc.subject | Neural Networks | en_US |
dc.subject | Pattern classification | en_US |
dc.subject | Speech recognition | en_US |
dc.title | A Novel Feature Extraction Method for Isolated Word Recognition Based on Nested Temporal Averaging | en_US |
dc.type | Article | en_US |