Support vector machines with the priorities method for speaker independent phoneme recognition

Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/17804

Title:	Support vector machines with the priorities method for speaker independent phoneme recognition
Authors:	Cutajar, Michelle Gatt, Edward Grech, Ivan Casha, Owen Micallef, Joseph
Keywords:	Support vector machines Automatic speech recognition Wavelets (Mathematics) Kernel functions Directed graphs
Issue Date:	2011
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Citation:	Cutajar, M., Gatt, E., Grech, I., Casha, O., & Micallef, J. (2012). Support vector machines with the priorities method for speaker independent phoneme recognition. IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Bilbao. 409-414.
Abstract:	A speaker independent phoneme recognition system, based on Support Vector Machines (SVMs) method was improved by adding a priority scheme to forecast the three most likely phonemes. The system helps improve the obtained recognitions rate . For the phoneme recognition system, four multiclass SVMs methods, the All- at-once, One-against-all, One-against-one, and the Directed Acyclic Graph SVM (DAGSVM), were designed. The One-against-one method performed best, achieving an accuracy of 53.70%. This accuracy was further increased to 75.41%, when the second and third priorities were considered in the priorities method. All tests were carried out on the TIMIT database.
URI:	https://www.um.edu.mt/library/oar//handle/123456789/17804
Appears in Collections:	Scholarly Works - FacICTMN

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