A Study of Acoustic Features in Arabic Speaker Identification under Noisy Environmental Conditions
One of the major parts of the voice recognition field is the choice of acoustic features which have to be robust against the variability of the speech signal, mismatched conditions, and noisy environments. Thus, different speech feature extraction techniques have been developed. In this paper, we in...
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| Format | Journal Article |
| Language | English |
| Published |
23.10.2021
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| Abstract | One of the major parts of the voice recognition field is the choice of
acoustic features which have to be robust against the variability of the speech
signal, mismatched conditions, and noisy environments. Thus, different speech
feature extraction techniques have been developed. In this paper, we
investigate the robustness of several front-end techniques in Arabic speaker
identification. We evaluate five different features in babble, factory and
subway conditions at the various signal to noise ratios (SNR). The obtained
results showed that two of the auditory feature i.e. gammatone frequency
cepstral coefficient (GFCC) and power normalization cepstral coefficients
(PNCC), unlike their combination performs substantially better than a
conventional speaker features i.e. Mel-frequency cepstral coefficients (MFCC). |
|---|---|
| AbstractList | One of the major parts of the voice recognition field is the choice of
acoustic features which have to be robust against the variability of the speech
signal, mismatched conditions, and noisy environments. Thus, different speech
feature extraction techniques have been developed. In this paper, we
investigate the robustness of several front-end techniques in Arabic speaker
identification. We evaluate five different features in babble, factory and
subway conditions at the various signal to noise ratios (SNR). The obtained
results showed that two of the auditory feature i.e. gammatone frequency
cepstral coefficient (GFCC) and power normalization cepstral coefficients
(PNCC), unlike their combination performs substantially better than a
conventional speaker features i.e. Mel-frequency cepstral coefficients (MFCC). |
| Author | Benhafid, Zhor Amrouche, Abderrahmane Zergat, Kawthar Yasmine |
| Author_xml | – sequence: 1 givenname: Zhor surname: Benhafid fullname: Benhafid, Zhor – sequence: 2 givenname: Kawthar Yasmine surname: Zergat fullname: Zergat, Kawthar Yasmine – sequence: 3 givenname: Abderrahmane surname: Amrouche fullname: Amrouche, Abderrahmane |
| BackLink | https://doi.org/10.48550/arXiv.2110.12304$$DView paper in arXiv |
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| Snippet | One of the major parts of the voice recognition field is the choice of
acoustic features which have to be robust against the variability of the speech
signal,... |
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| SubjectTerms | Computer Science - Sound |
| Title | A Study of Acoustic Features in Arabic Speaker Identification under Noisy Environmental Conditions |
| URI | https://arxiv.org/abs/2110.12304 |
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