Feature extraction with mel scale separation method on noise audio recordings
share
This paper focuses on improving the accuracy of noise audio recordings. High-quality audio recording, extraction using the mel frequency cepstral coefficients (MFCC) method produces high accuracy. While the low-quality is because of noise, the accuracy is low. Improved accuracy by investigating the effect of bandwidth on the mel scale. The proposed improvement uses the mel scale separation methods into two frequency channels (MFCC dual channel). For the comparison method using the mel scale bandwidth without separation (MFCC single-channel). Feature analysis using k-mean clustering. The data uses a noise variance of up to -16 dB. Testing on the MFCC single channel method for -16 dB noise has an accuracy of 47.5 an accuracy better of 76.25 to reduce noise before extraction. The result is that the MFCC single-channel method has an accuracy of 82.5 accuracy better of 83.75 single-channel method has an accuracy of 92.5 has an accuracy better of 97.5 bandwidth to increase accuracy. The MFCC dual-channel method has higher accuracy.
READ FULL TEXT
