Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/17782| Title: | Hardware-based support vector machine for phoneme classification |
| Authors: | Cutajar, Michelle Gatt, Edward Grech, Ivan Casha, Owen Micallef, Joseph |
| Keywords: | Support vector machines Field programmable gate arrays Wavelets (Mathematics) Radial basis functions Automatic speech recognition |
| Issue Date: | 2013 |
| Publisher: | Institute of Electrical and Electronics Engineers Inc. |
| Citation: | Cutajar, M., Gatt, E., Grech, I., Casha, O., & Micallef, J. (2013). Hardware-based support vector machine for phoneme classification. Eurocon 2013, Zagreb. 1701-1708. |
| Abstract: | This paper presents the design of a digital hardware implementation based on Support Vector Machines (SVMs), for the task of multi-speaker phoneme recognition. The One-against-one multiclass SVM method, with the Radial Basis Function (RBF) kernel was considered. Furthermore, a priority scheme was also included in the architecture, in order to forecast the three most likely phonemes. The designed system was synthesised on a Xilinx Virtex-II XC2V3000 FPGA, and evaluated with the TIMIT corpus. This phoneme recognition system is intended to be implemented on a dedicated chip, along with the Discrete Wavelet Transforms (DWTs) for feature extraction, to further improve the resultant performance. |
| URI: | https://www.um.edu.mt/library/oar//handle/123456789/17782 |
| Appears in Collections: | Scholarly Works - FacICTMN |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Hardware-based Support Vector Machine for Phoneme Classification.pdf Restricted Access | Hardware-based support vector machine for phoneme classification | 490.87 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.