Enhanced forensic speaker verification using multi-run ICA in the presence of environmental noise and reverberation conditions

Ahmed Kamil Hasan Al-Ali, Bouchra Senadji, Ganesh R. Naik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The performance of forensic speaker verification degrades severely in the presence of high levels of environmental noise and reverberation conditions. Multiple channel speech enhancement algorithms are a possible solution to reduce the effect of environmental noise from the noisy speech signals. Although multiple speech enhancement algorithms such as multi-run independent component analysis (ICA) were used in previous studies to improve the performance of recognition in biosignal applications, the effectiveness of multi-run ICA algorithm to improve the performance of noisy forensic speaker verification under reverberation conditions has not been investigated yet. In this paper, the multi-run ICA algorithm is used to enhance the noisy speech signals by choosing the highest signal to interference ratio (SIR) of the mixing matrix from different mixing matrices generated by iterating the fast ICA algorithm for several times. Wavelet-based mel frequency cepstral coefficients (MFCCs) feature warping approach is applied to the enhanced speech signals to extract the robust features to environmental noise and reverberation conditions. The state-of-The-Art intermediate vector (i-vector) and probabilistic linear discriminant analysis (PLDA) are used as a classifier in our approach. Experimental results show that forensic speaker verification based on the multi-run ICA algorithm achieves significant improvements in equal error rate (EER) of 60.88%, 51.84%, 66.15% over the baseline noisy speaker verification when enrolment speech signals reverberated at 0.15 sec and the test speech signals were mixed with STREET, CAR and HOME noises respectively at-10 dB signal to noise ratio (SNR).

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA 2017)
Place of PublicationMalaysia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages174-179
Number of pages6
ISBN (Electronic)9781509055593, 9781509055586
ISBN (Print)9781509055609
DOIs
Publication statusPublished - 1 Dec 2017
Externally publishedYes
Event5th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017 - Kuching, Sarawak, Malaysia
Duration: 12 Sep 201714 Sep 2017

Publication series

NameProceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017

Conference

Conference5th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017
CountryMalaysia
CityKuching, Sarawak
Period12/09/1714/09/17

Keywords

  • multi-run ICA algorithm
  • Noisy forensic speaker verification
  • reverberation

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    Al-Ali, A. K. H., Senadji, B., & Naik, G. R. (2017). Enhanced forensic speaker verification using multi-run ICA in the presence of environmental noise and reverberation conditions. In Proceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA 2017) (pp. 174-179). (Proceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSIPA.2017.8120601