This paper introduces the Laplace algorithm for de-noising in the cepstrum domain with applications to speech recognition. Our method uses Gaussian mixture priors for clean speech and noise cepstra and assumes that speech and noise mix linearly in the spectrum domain. The Laplace algorithm involves two steps (a) computing the posterior mode of the observed noisy cepstra and (b) Gaussian approxi...

─ It is currently believed that nanometerscale internal refractive index fluctuations within biological cells change significantly during the initial stages of ultra early-stage cancer development well in advance of these changes becoming more pronounced and histologically detectable. Here, backscattered cepstral results of photonic nanojet-illuminated cells are investigated as a means to offer...

Formant frequencies have rarely been used as acoustic features for speech recognition, in spite of their phonetic significance. For some speech sounds one or more of the formants may be so badly defined that it is not useful to attempt a frequency measurement. Also, it is often difficult to decide which formant labels to attach to particular spectral peaks. This paper describes a new method of ...

The mel-scaled cepstrum is a signal representation scheme used in the analysis of speech signals. Due to its reported superior performance, especially under adverse conditions, it is becoming an increasingly popular choice as feature extraction front end to spoken language systems. Having evolved over a period of more than fifty years, the mel-scaled cepstrum owes part of its heritage to the pa...

Cardiac disease is a big reason of premature dying. A significant amount of research and development effort has been devoted on detection of cardiovascular disease but still cannot get the control on death rate of cardiac disease. In this paper, we successfully analyze the parameter, which is helpful in detection of Heart disease. Diseases can be categorized according to1) action potential (suc...

This paper provides analysis of kepstrum (known elsewhere as complex cepstrum) and its real-time application to noise cancellation. The method uses kepstrum estimation for identification of the ratio of acoustic path transfer functions between two microphones and efficient processing technique for real-time processing. It is applied to the front-end of speech enhancement method, the Griffiths a...

Automatic voice/music segment detection is expected for various applications. For the general applications of voice recognition and dictation, input voice for the recognition is needed to detect and remove music section automatically. In order to detect voice and music segments, where sound data contains both voice and music, this paper proposes weighted Block Cepstrum Flux (BCF) and optimizes ...

Most of the features of Cover Song Identification (CSI), for example, Pitch Class Profile (PCP) related features, are based on the musical facets shared among cover versions: melody evolution and harmonic progression. In this work, the perceptual feature was studied for CSI. Our idea was to modify the Perceptual Linear Prediction (PLP) model in the field of Automatic Speech Recognition (ASR) by...

This paper reports comparative evaluations of twelve typical methods of estimating fundamental frequency (F0) over huge speech-sound datasets in artificial reverberant environments. They involve several classic algorithms such as Cepstrum, AMDF, LPC, and modified autocorrelation algorithms. Other methods involve a few modern instantaneous amplitudeand/or frequency-based algorithms, such as STRA...