Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107270
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical and Electronic Engineering | en_US |
dc.creator | Li, N | en_US |
dc.creator | Mak, MW | en_US |
dc.date.accessioned | 2024-06-13T01:05:01Z | - |
dc.date.available | 2024-06-13T01:05:01Z | - |
dc.identifier.isbn | 978-1-4799-9988-0 (Electronic) | en_US |
dc.identifier.isbn | 978-1-4799-9987-3 (USB) | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/107270 | - |
dc.description | 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 20-25 March 2016, Shanghai, China | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | ©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication N. Li and M. -W. Mak, "SNR-invariant PLDA with multiple speaker subspaces," 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, 2016, pp. 5565-5569 is available at https://doi.org/10.1109/ICASSP.2016.7472742. | en_US |
dc.subject | I-vectors | en_US |
dc.subject | SNR subspaces | en_US |
dc.subject | SNR-invariant PLDA | en_US |
dc.subject | Speaker subspaces | en_US |
dc.subject | Speaker verification | en_US |
dc.title | SNR-invariant PLDA with multiple speaker subspaces | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.spage | 5565 | en_US |
dc.identifier.epage | 5569 | en_US |
dc.identifier.doi | 10.1109/ICASSP.2016.7472742 | en_US |
dcterms.abstract | To deal with the mismatch between the enrollment and test utterances caused by noise with different signal-to-noise ratios (SNR), we have recently proposed an SNR-invariant PLDA model for robust speaker verification. In the model, SNR-specific information were separated from speaker-specific information through marginalizing out the SNR factors during the scoring process. However, this modeling approach assumes that speaker variabilities can be captured by a single speaker subspace regardless of the noise level of the utterances. We will show in this paper that i-vectors extracted from utterances with different noise levels will shift to different regions of the i-vector space and that i-vectors extracted from utterances having similar SNR tend to cluster together. In view of this observation, we propose introducing multiple speaker subspaces to the SNR-invariance PLDA model and use multiple covariance matrices to represent SNR-dependent channel variability. Through NIST 2012 SRE, this paper demonstrates that this finer and more precise modeling of speaker and SNR variabilities leads to better performance when compared with the conventional PLDA and SNR-invariant PLDA. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | In Proceedings of 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 20-25 March 2016, Shanghai, China, p. 5565-5569 | en_US |
dcterms.issued | 2016 | - |
dc.identifier.scopus | 2-s2.0-84973367336 | - |
dc.relation.conference | International Conference on Acoustics, Speech, and Signal Processing [ICASSP] | en_US |
dc.description.validate | 202404 bckw | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | EIE-0863 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 9574627 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Conference Paper |
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File | Description | Size | Format | |
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Mak_Snr-Invariant_Plda_Multiple.pdf | Pre-Published version | 938.8 kB | Adobe PDF | View/Open |
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