ROBUST HYBRID FEATURES BASED TEXT INDEPENDENT SPEAKER IDENTIFICATION SYSTEM OVER NOISY ADDITIVE CHANNEL

المؤلفون

  • Ali Muayad Jalil Electrical Engineering Department, Mustansiriyah University, Baghdad, Iraq مؤلف
  • Fadhel Sahib Hasan Electrical Engineering Department, Mustansiriyah University, Baghdad, Iraq مؤلف
  • Hesham Adnan Alabbasi Computer Engineering Department, Mustansiriyah University, Baghdad, Iraq مؤلف

DOI:

https://doi.org/10.31272/jeasd.24.4.7

الكلمات المفتاحية:

robust speaker identification، robust feature extraction، PNCC، GFCC، FW، UBM-GMM

الملخص

Robustness of speaker identification systems over additive noise is crucial for real-world applications. In this paper, two robust features named Power Normalized Cepstral Coefficients (PNCC) and Gammatone Frequency Cepstral Coefficients (GFCC) are combined together to improve the robustness of speaker identification system over different types of noise. Universal Background Model Gaussian Mixture Model (UBM-GMM) is used as a feature matching and a classifier to identify the claim speakers. Evaluation results show that the proposed hybrid feature improves the performance of identification system when compared to conventional features over most types of noise and different signal-to-noise ratios.

التنزيلات

Key Dates

منشور

2020-07-01

إصدار

مجلد 24 عدد 4 (2020): Journal of Engineering and Sustainable Development

القسم

Articles

الرخصة

Creative Commons License

هذا العمل مرخص بموجب Creative Commons Attribution 4.0 International License.

The Journal of Engineering and Sustainable Development is an open-access journal that all contents are free of charge. Articles of this journal are licensed under the terms of the Creative Commons Attribution International Public License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) that licensees are unrestrictly allowed to search, download, share, distribute, print, or link to the full texts of the articles, crawl them for indexing and reproduce any medium of the articles provided that they give the author(s) proper credits (citation). The journal allows the author(s) to retain the copyright of their published article.
Creative Commons-Attribution (BY)

كيفية الاقتباس

Muayad Jalil, A. ., Sahib Hasan, F. ., & Adnan Alabbasi, H. . (2020). ROBUST HYBRID FEATURES BASED TEXT INDEPENDENT SPEAKER IDENTIFICATION SYSTEM OVER NOISY ADDITIVE CHANNEL. مجلة الهندسة والتنمية المستدامة, 24(4), 56-70. https://doi.org/10.31272/jeasd.24.4.7

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