Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Multi-disciplinary Studies | en_US |
| dc.contributor | Department of Electronic Engineering | en_US |
| dc.creator | Cheung, Man-yee Miranda | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/396 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Decision strategies for robust speaker verification | en_US |
| dcterms.abstract | In this dissertation, a new decision strategy based on statistical post-processing of speakers' scores is proposed for speaker verification. Specifically, the dissertation explores the possibility of enhancing the state-of-the-art speaker verification systems by taking into account the discrepancy between speaker's scores and his/her decision threshold. To this end, speaker's scores are ranked according to their proximity to the decision threshold. Non-parametric statistical tests, such as the Wilcoxon signed rank test, are applied to the ranked scores. The Wilcoxon signed rank test is presented in detail and the reasons for choosing it to do the post-processing of speakers' scores are explained. Experimental results, based on 76 speakers of the TIMIT corpus, show that the performance of a vector quantization-based speaker verification system is improved after applying the Wilcoxon test. The method is very general and can be easily extended to other speaker verification systems. | en_US |
| dcterms.extent | vi, 68 leaves : ill. ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2001 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Speech processing systems | en_US |
| dcterms.LCSH | Automatic speech recognition | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b15995793.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.14 MB | Adobe PDF | View/Open |
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