Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/17875
Title: | Design of a hardware-based discrete wavelet transform architecture for phoneme recognition |
Authors: | Cutajar, Michelle Gatt, Edward Grech, Ivan Casha, Owen Micallef, Joseph |
Keywords: | Field programmable gate arrays Speech processing systems Wavelets (Mathematics) Computer architecture |
Issue Date: | 2014 |
Publisher: | IEEE Computer Society |
Citation: | Cutajar, M., Gatt, E., Grech, I., Casha, O., & Micallef, J. (2014). Design of a hardware-based discrete wavelet transform architecture for phoneme recognition. 6th International Symposium on Communications, Control and Signal Processing (ISCCSP), Athens. 554-557. |
Abstract: | This paper presents the design of a digital hardware implementation based on Discrete Wavelet Transforms (DWTs) for the task of feature extraction in a multi-speaker phoneme recognition system. This is the first research where the design of a hardware-based DWT design is directed towards a speech recognition application. In the proposed architecture, the lifting-scheme approach employing the orthogonal Daubechies wavelet of order 5 was considered. The designed system was synthesised on a Xilinx Virtex-II XC2V3000 FPGA, and evaluated with the TIMIT corpus. This hardware-based DWT architecture is then intended to be implemented on a dedicated chip, along with the hardware implementation of the classification stage of the proposed phoneme recognition system, in order to further improve the resultant performance. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/17875 |
Appears in Collections: | Scholarly Works - FacICTMN |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Design of a hardware-based discrete wavelet transform architecture for phoneme recognition.pdf Restricted Access | Design of a hardware-based discrete wavelet transform architecture for phoneme recognition | 215.16 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.