Contrary to expectations that the coronavirus pandemic would terminate quickly, number of people infected with virus did not decrease worldwide and coronavirus-related deaths continue occur every day. The standard COVID-19 diagnostic test technique used today, PCR testing, requires professional staff equipment, which is expensive takes a long time produce results. In this paper, we propose feat...

Automatic detection of emotions has been evaluated using standard Mel-frequency Cepstral Coefficients, MFCCs, and a variant, MFCC-low, calculated between 20 and 300 Hz, in order to model pitch. Also plain pitch features have been used. These acoustic features have all been modeled by Gaussian mixture models, GMMs, on the frame level. The method has been tested on two different corpora and langu...

This work proposes a novel method of predicting formant frequencies from a stream of mel-frequency cepstral coefficients (MFCC) feature vectors. Prediction is based on modelling the joint density of MFCCs and formant frequencies using a Gaussian mixture model (GMM). Using this GMM and an input MFCC vector, two maximum a posteriori (MAP) prediction methods are developed. The first method predict...

Previously, we proposed a speaker recognition system using a combination of MFCC-based vocal tract feature and phase information which includes rich vocal source information. In this paper, we investigate the efficiency of combination of various vocal tract features (MFCC and LPCC) and vocal source features (phase and LPC residual) for normal-duration and short-duration utterance. The Japanese ...

Arc faults pose challenges to electric safety, which can cause serious fire hazards. However, the commonly used arc fault detection method is prone nuisance tripping. This paper proposed a hybrid based on improved Mel-Frequency Ceptral Coefficients (MFCC) for preprocessing and neural network model identification called ARC_MFCC. As per IEC 62606, twelve different loads/scenarios are considered ...

Automatic detection of emotions has been evaluated using standard Mel-frequency Cepstral Coefficients, MFCCs, and a variant, MFCC-low, that is calculated between 20 and 300 Hz in order to model pitch. Plain pitch features have been used as well. These acoustic features have all been modeled by Gaussian mixture models, GMMs, on the frame level. The method has been tested on two different corpora...

Automatic Speaker Recognition (ASR) is an economic tool for voice biometrics because of availability of low cost and powerful processors. For an ASR system to be successful in practical environments, it must have high mimic resistance, i.e., the system should not be defeated by determined mimics which may be either identical twins or professional mimics. In this paper, we demonstrate the effect...

In this paper, hum of a person is used in voice biometric system. In addition, recently proposed feature set, i.e., Variable length Teager Energy Based Mel Frequency Cepstral Coefficients (VTMFCC), is found to capture perceptually meaningful source-like information from hum signal. For person recognition, MFCC gives EER of 13.14% and %ID of 64.96%. A reduction in equal error rate (EER) by 0.2% ...

Information world meet many confronts nowadays and one such, is data retrieval from a multidimensional and heterogeneous data set. Han & et al carried out a trail for the mentioned challenge. A novel feature co-selection for web document clustering is proposed by them, which is called Multitype Features Co-selection for Clustering (MFCC). MFCC uses intermediate clustering results in one type of...