@inproceedings{b90a606748a24acf8c3f43abc76551fa,
title = "DWT-MFCC Method for Speaker Recognition System with Noise",
abstract = "The Mel-frequency Cepstral Coefficients (MFCC) method is the most popular method and has good performance as a feature extraction to date. But based on the simulation results, it is known that the speaker recognition system that uses MFCC as a feature extraction has low accuracy when applied to voice containing noise. So in this study, we propose the DWT-MFCC method to overcome this problem. The simulation results show that the DWT-MFCC method has higher accuracy compare with conventinal MFCC method when applied as feature extraction in the speaker recognition system with SNR from 15 to 40 dB.",
keywords = "biometric, feature extraction, MFCC, Speaker recognition, wavelet",
author = "Fetty Amelia and Dadang Gunawan",
year = "2019",
month = jun,
day = "1",
doi = "10.1109/ICSCC.2019.8843660",
language = "English",
series = "2019 7th International Conference on Smart Computing and Communications, ICSCC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 7th International Conference on Smart Computing and Communications, ICSCC 2019",
address = "United States",
note = "7th International Conference on Smart Computing and Communications, ICSCC 2019 ; Conference date: 28-06-2019 Through 30-06-2019",
}