Cepstrum

About: Cepstrum is a research topic. Over the lifetime, 3346 publications have been published within this topic receiving 55742 citations.

Automated Sound Analysis System for Home Telemonitoring using Shifted Delta Cepstral Features

Abstract: With an ageing world population and a corresponding demand for aged care, interest in the development of home telemonitoring systems has increased greatly in recent years. Automated sound analysis systems have been considered as an alternative for video monitoring in the interests of privacy. This paper investigates the use of frequency domain features, namely the Mel frequency cepstral coefficients (MFCC), in identifying and monitoring sounds of daily activities of elderly persons. A Gaussian mixture model (GMM) is used as the back-end system classifier. We also include a new compact feature set, the shifted delta cepstrum (SDC), improving our results. This model achieves a classification accuracy of 91.58%, distinguishing between 19 different real-world sounds.

Dimensionality reduction for voice disorders identification system based on Mel Frequency Cepstral Coefficients and Support Vector Machine

Abstract: Nowadays, due to the severe daily activities and vocal abuse, many diseases affect the mechanism of voice production which causes pathological voices. Therefore, the identification of voice diseases becomes a real challenge. In this context, the automatic speech recognition can provide great results as a complementary tool to other medical techniques. This paper proposes a reliable algorithm based on short-term cepstral parameters, Linear Discriminant Analysis (LDA) as dimensionality reduction method and Support Vector Machine (SVM) as classifier. A full comparative study is established and the system performance is evaluated in terms of accuracy, sensitivity, specificity, precision and Area Under Curve (AUC). Our findings demonstrate that the detection of voice disorders can be efficient using only the original Mel Frequency Cepstral Coefficients (MFCC) ignoring their first and second derivative.

A Method for Subsample Fetal Heart Rate Estimation Under Noisy Conditions

Abstract: In this paper, we consider a new approach for estimating the fundamental period in fetal ECG waveforms. The fundamental period contains information that is indicative of the physiological condition of the fetus such as hypoxia and acidemia. Our method is based on the minimization of a cost function that measures the differences between the discrete Fourier transform (DFT) of the fetal ECG waveform and the DFTs of its circularly shifted forms. By using the linear phase shift property of the DFT, we show that the minimization of this cost function is equivalent to finding the cosine waveform that matches best to the ECG power spectrum. The optimal cosine waveform is then used to estimate the fundamental period. We expand this method and discuss estimation of the fundamental period with subsample precision. Subsample estimates may be useful especially when a low sampling rate is used for a long period of monitoring. Comparison of performance of this method with Cepstrum and average mIn this paper, we consider a new approach for estimating the fundamental period in fetal ECG waveforms. The fundamental period contains information that is indicative of the physiological condition of the fetus such as hypoxia and acidemia. Our method is based on the minimization of a cost function that measures the differences between the discrete Fourier transform (DFT) of the fetal ECG waveform and the DFTs of its circularly shifted forms. By using the linear phase shift property of the DFT, we show that the minimization of this cost function is equivalent to finding the cosine waveform that matches best to the ECG power spectrum. The optimal cosine waveform is then used to estimate the fundamental period. We expand this method and discuss estimation of the fundamental period with subsample precision. Subsample estimates may be useful especially when a low sampling rate is used for a long period of monitoring. Comparison of performance of this method with Cepstrum and average magnitude difference function methods shows that our approach achieves very accurate period estimation results for both simulated and real fetal EGC waveforms that are taken at different stages of the gestation under noisy conditions.agnitude difference function methods shows that our approach achieves very accurate period estimation results for both simulated and real fetal EGC waveforms that are taken at different stages of the gestation under noisy conditions.