The Impact of Low-Pass Filter in Speaker Identification
Rizky Ahmad, Suyanto Suyanto · 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) · 2019
Speaker identification model commonly uses Mel Frequency Ceptral Coefficient (MFCC) and Gaussian Mixture Model (GMM). Due to many weaknesses from previous studies for noised speech, here a low-pass-filter is proposed to reduce the high-frequency signals. The low-pass-filter is expected to calculate cut-offs. Experimental results show that the low-pass filter significantly improves the accuracy of sound detection for the high noised signal.