Power Wavelet Cepstral Coefficients (PWCC): An Accurate Auditory Model-Based Feature Extraction Method for Robust Speaker Recognition

Power Wavelet Cepstral Coefficients (PWCC): An Accurate Auditory Model-Based Feature Extraction Method for Robust Speaker Recognition

Human capability for Speaker Recognition (SR) exceeds recent machine learning approaches, even in noisy environments. To bridge this gap, researchers investigate the human auditory system to support machine learning algorithm performance. The paper introduces a novel feature extraction method, named...

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Bibliographic Details
Main Authors: Youssef Zouhir, Mohamed Zarka, Kais Ouni, Lilia El Amraoui
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Speaker recognition
machine learning
GMM-UBM
feature extraction
MFCC
PNCC
Online Access:https://ieeexplore.ieee.org/document/11024023/
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https://ieeexplore.ieee.org/document/11024023/

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