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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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Proceedings ArticleDOI
01 Apr 1985
TL;DR: Results suggest that the fourth-root spectrum and the amplitude spectrum PDAs are lesssensitive to noise than the cepstrum PDA and less sensitive to strong first formants than the autocorrelation PDA.
Abstract: The performance of double-transform pitch determination algorithms (PDAs) with frequency-domain nonlinear distortion is investigated. This PDA principle comprises well-known PDAs, such as the autocorrelation PDA and the cepstrum PDA. Besides these two, the amplitude spectrum and the fourth-root spectrum PDAs were implemented and tested under various environmental conditions (clean signal, telephone-quality signal, and signal degraded by additive Gaussian noise). First results suggest that the fourth-root spectrum and the amplitude spectrum PDAs are less sensitive to noise than the cepstrum PDA and less sensitive to strong first formants than the autocorrelation PDA.

24 citations

Journal ArticleDOI
TL;DR: A modified approach that is less sensitive to these effects of noise, foreshortening differences, and photometric variations on existing cepstral correspondence techniques is developed for textured scenes, and analytical arguments for its robustness are developed.
Abstract: This paper analyses the performance of cepstral approaches for solving the stereo correspondence problem. A quantitative analysis of the effects of noise, foreshortening differences, and photometric variations on existing cepstral correspondence techniques is presented. A modified approach that is less sensitive to these effects is developed for textured scenes, and analytical arguments for its robustness are developed. The results of a comparative study of the new cepstral technique, the original cepstral algorithm and the cross-correlation approach are shown and discussed. The performance of the new method is experimentally verified on textured surfaces.

24 citations

Journal ArticleDOI
TL;DR: A hybrid noise resilient F0 detection algorithm named BaNa that combines the approaches of harmonic ratios and Cepstrum analysis is presented that achieves the lowest Gross Pitch Error (GPE) rate among all the algorithms.
Abstract: Fundamental frequency (F0) is one of the essential features in many acoustic related applications. Although numerous F0 detection algorithms have been developed, the detection accuracy in noisy environments still needs improvement. We present a hybrid noise resilient F0 detection algorithm named BaNa that combines the approaches of harmonic ratios and Cepstrum analysis. A Viterbi algorithm with a cost function is used to identify the F0 value among several F0 candidates. Speech and music databases with eight different types of additive noise are used to evaluate the performance of the BaNa algorithm and several classic and state-of-the-art F0 detection algorithms. Results show that for almost all types of noise and signal-to-noise ratio (SNR) values investigated, BaNa achieves the lowest Gross Pitch Error (GPE) rate among all the algorithms. Moreover, for the 0 dB SNR scenarios, the BaNa algorithm is shown to achieve 20% to 35% GPE rate for speech and 12% to 39% GPE rate for music. We also describe implementation issues that must be addressed to run the BaNa algorithm as a real-time application on a smartphone platform.

24 citations

Journal Article
TL;DR: In this article, the authors introduce envelope and cepstrum analyses to identify local machinery faults, and demonstrate their properties by using a couple of practical examples, such as rotating machinery parts.
Abstract: All rotating machinery parts wear, as does ancient wisdom. Envelope and cepstrum analyses tend to be overlooked, but they are still useful tools to identify local machinery faults. The intent of this article is to introduce these two tools in a pragmatic way and to demonstrate their properties by using a couple of practical examples.

24 citations

Proceedings ArticleDOI
03 Oct 1996
TL;DR: It is shown that the main cause for the superiority of CMS compared to RasTA is the phase distortion introduced by the RASTA filter.
Abstract: We compared three different channel normalisation (CN) methods in the context of a connected digit recognition task over the phone: cepstrum mean substraction (CMS), RASTA filtering and the Gaussian dynamic cepstrum representation (GDCR). Using a small set of context independent (CI) continuous Gaussian mixture hidden Markov models (HMMs), we found that CMS and RASTA outperformed the GDCR technique. We show that the main cause for the superiority of CMS compared to RASTA is the phase distortion introduced by the RASTA filter. Recognition results for a phase corrected RASTA technique are identical to those of CMS. Our results indicate that an ideal cepstrum based CN method should: (1) effectively remove the DC component; (2) at least preserve modulation frequencies in the range 2-16 Hz; and (3) introduce no phase distortion in case CI HMMs are used for recognition.

24 citations


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