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Cepstrum

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


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Journal ArticleDOI
TL;DR: The efficiency of specmurt analysis is experimentally demonstrated through generation of a piano-roll-like display from a polyphonic music signal and automatic sound-to-MIDI conversion and compared with manually annotated MIDI data.
Abstract: This paper introduces a new music signal processing method to extract multiple fundamental frequencies, which we call specmurt analysis. In contrast with cepstrum which is the inverse Fourier transform of log-scaled power spectrum with linear frequency, specmurt is defined as the inverse Fourier transform of linear power spectrum with log-scaled frequency. Assuming that all tones in a polyphonic sound have a common harmonic pattern, the sound spectrum can be regarded as a sum of linearly stretched common harmonic structures along frequency. In the log-frequency domain, it is formulated as the convolution of a common harmonic structure and the distribution density of the fundamental frequencies of multiple tones. The fundamental frequency distribution can be found by deconvolving the observed spectrum with the assumed common harmonic structure, where the common harmonic structure is given heuristically or quasi-optimized with an iterative algorithm. The efficiency of specmurt analysis is experimentally demonstrated through generation of a piano-roll-like display from a polyphonic music signal and automatic sound-to-MIDI conversion. Multipitch estimation accuracy is evaluated over several polyphonic music signals and compared with manually annotated MIDI data.

60 citations

Proceedings ArticleDOI
27 Sep 2004
TL;DR: In this article, the authors compared several features of vibration signals as indicators of broken rotor bar of a 35 kW induction motor with regular fast Fourier transform (FFT) based power spectrum density (PSD) estimation.
Abstract: Vibration monitoring is studied for fault diagnostics of an induction motor. Several features of vibration signals are compared as indicators of broken rotor bar of a 35 kW induction motor. Regular fast Fourier transform (FFT) based power spectrum density (PSD) estimation is compared to signal processing with higher order spectra (HOS), cepstrum analysis and signal description with autoregressive (AR) modelling. The fault detection routine and feature comparison is carried out with support vector machine (SVM) based classification. The best method for feature extraction seems to be the application of AR coefficients. The result is found out with real measurement data from several motor conditions and load situations.

60 citations

Journal ArticleDOI
TL;DR: Experimental results show that the proposed system is effective in suppressing both reverberation and noise while improving the speech quality, and the achieved improvements are particularly significant in conditions with high reverberation times.
Abstract: This paper presents a system aiming at joint dereverberation and noise reduction by applying a combination of a beamformer with a single-channel spectral enhancement scheme. First, a minimum variance distortionless response beamformer with an online estimated noise coherence matrix is used to suppress noise and reverberation. The output of this beamformer is then processed by a single-channel spectral enhancement scheme, based on statistical room acoustics, minimum statistics, and temporal cepstrum smoothing, to suppress residual noise and reverberation. The evaluation is conducted using the REVERB challenge corpus, designed to evaluate speech enhancement algorithms in the presence of both reverberation and noise. The proposed system is evaluated using instrumental speech quality measures, the performance of an automatic speech recognition system, and a subjective evaluation of the speech quality based on a MUSHRA test. The performance achieved by beamforming, single-channel spectral enhancement, and their combination are compared, and experimental results show that the proposed system is effective in suppressing both reverberation and noise while improving the speech quality. The achieved improvements are particularly significant in conditions with high reverberation times.

60 citations

Journal ArticleDOI
TL;DR: In this paper, the authors apply autoregressive spectral analysis to the log spectrum of short-period seismograms to determine the depth below the earth's surface at which the seismic event originated.
Abstract: This paper discusses the practical application of autoregressive spectral analysis to three different geophysical data sets. In all cases the amount of available data was limited so that autoregressive methods might give more detailed spectra than those obtainable by the classical windowed spectral estimate methods. For each series, the Burg technique, which guarantees positive-definite autocorrelation functions, is used to determine the prediction error coefficients. The degree of spectral instability known to result from the use of Burg's algorithm is not crucial to our results. Algorithms due to Akaike and Parzen are applied to the time series to aid in order-number determination. For the first example, autoregressive spectral analysis of a complex time series is applied to the log spectrum of short-period seismograms. The resultant spectrum, the so-called complex cepstrum, allows one to determine the depth below the earth's surface at which the seismic event originated. The other examples concern the analysis of real time series due to two somewhat unusual data sets. One of these is the analysis of the time rate at which earthquakes occur. The purpose is to determine if periodicities exist that correspond to known astronomical and terrestrial rotational periods. The other is a study of biological and chemical parameters measured in core samples of oceanbottom sediments where displacement down the core is calibrated in geological time. The measurements directly infer the amount of ice on the earth's surface.

60 citations

Journal ArticleDOI
TL;DR: A principal components analysis was performed on a set of acoustic, aerodynamic, perceptual and laryngoscopic data obtained from 87 dysphonic patients, finding harmonics-to-noise ratio in the formant zone and magnitude of the dominant cepstrum peak seem to integrate the effects of both principal components.

60 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202386
2022206
202160
202096
2019135
2018130