@inproceedings{8b1d1edacc064583905983b9bc5ef847,
title = "Cubic Law and MAP Compensation Techniques for Robust Text-Independent Speaker Identification",
abstract = "Automatic speaker recognition is drastically degraded in presence of noise. This paper focuses on the application of the cubic law and histogram mapping for the text-independent speaker recognition task. Our aim of this study is the application of these two methods in the feature extraction stage of the Power-Normalized Cepstral Coefficients (PNCC) and the conventional Mel Frequency Cepstral Coefficients (MFCC) techniques. Recognition results show that the cubic law combined with the histogram mapping improve the recognition rates.",
keywords = "cubic law, histogram mapping, noise robustness, PNCC, speaker identification",
author = "Harry Anacleto and David Chavez",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 27th International Conference on Systems, Signals and Image Processing, IWSSIP 2020 ; Conference date: 01-07-2020 Through 03-07-2020",
year = "2020",
month = jul,
doi = "10.1109/IWSSIP48289.2020.9145319",
language = "English",
series = "International Conference on Systems, Signals, and Image Processing",
publisher = "IEEE Computer Society",
pages = "387--392",
editor = "Paiva, {Anselmo C.} and Aura Conci and Geraldo Braz and Almeida, {Joao Dallyson S.} and Fernandes, {Leandro A. F.}",
booktitle = "Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, IWSSIP 2020",
}