Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/17646
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cutajar, Michelle | - |
dc.contributor.author | Gatt, Edward | - |
dc.contributor.author | Grech, Ivan | - |
dc.contributor.author | Casha, Owen | - |
dc.contributor.author | Micallef, Joseph | - |
dc.date.accessioned | 2017-03-20T10:56:26Z | - |
dc.date.available | 2017-03-20T10:56:26Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Cutajar, M., Gatt, E., Grech, I., Casha, O., & Micallef, J. (2012). Comparison of different multiclass SVM methods for speaker independent phoneme recognition. 5th International Symposium on Communications, Control and Signal Processing, Rome. 1-5. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/17646 | - |
dc.description.abstract | Four multiclass Support Vector Machines (SVMs) methods were designed for the task of speaker independent phoneme recognition. These are the All-at-once, One-against-all, One-against-one, and the Directed Acyclic Graph SVM (DAGSVM). The Discrete Wavelet Transform (DWT) 8 frequency band power percentages are used for feature extraction. All tests were carried out on the TIMIT database. Comparable recognition rates were obtained from all designed systems. However, the One-against-One method performed best, achieving an accuracy of 53.70% for multi-speaker unlimited vocabulary speech. The phoneme recognition system, adopting the DWT and the One-against-one method, are intended to be implemented on a dedicated chip. The dedicated chip will improve the speed performance by approximately 100 times when comparing the hardware setup with the software implementation. This is obtained by providing the hardware parallelism, which accommodates the algorithms that have been used. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Support vector machines | en_GB |
dc.subject | Automatic speech recognition | en_GB |
dc.subject | Speech processing systems | en_GB |
dc.subject | Kernel functions | en_GB |
dc.title | Comparison of different multiclass SVM methods for speaker independent phoneme recognition. | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.bibliographicCitation.conferencename | 5th International Symposium on Communications, Control and Signal Processing | en_GB |
dc.bibliographicCitation.conferenceplace | Rome, Italy, 2-4/05/2012 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1109/ISCCSP.2012.6217772 | - |
Appears in Collections: | Scholarly Works - FacICTMN |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Comparison of different multiclass SVM methods for speaker independent phoneme recognition.pdf Restricted Access | Comparison of different multiclass SVM methods for speaker independent phoneme recognition | 923.17 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.