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Relevant bibliographies by topics / Cepstral Mean Subtraction

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Journal articles
Dissertations / Theses
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Academic literature on the topic 'Cepstral Mean Subtraction'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Cepstral Mean Subtraction"

1

Yang, Pu, Yingchun Yang, and Zhaohui Wu. "Robust speaker recognition using glottal information‐based cepstral mean subtraction." Journal of the Acoustical Society of America 116, no. 4 (2004): 2481–82. http://dx.doi.org/10.1121/1.4784912.

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2

Shabtai, Noam R., Boaz Rafaely, and Yaniv Zigel. "The effect of reverberation on the performance of cepstral mean subtraction in speaker verification." Applied Acoustics 72, no. 2-3 (2011): 124–26. http://dx.doi.org/10.1016/j.apacoust.2010.09.009.

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3

Veisi, Hadi, and Hossein Sameti. "The integration of principal component analysis and cepstral mean subtraction in parallel model combination for robust speech recognition." Digital Signal Processing 21, no. 1 (2011): 36–53. http://dx.doi.org/10.1016/j.dsp.2010.07.004.

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4

Boulmaiz, Amira, Djemil Messadeg, Noureddine Doghmane, and Abdelmalik Taleb-Ahmed. "Design and Implementation of a Robust Acoustic Recognition System for Waterbird Species using TMS320C6713 DSK." International Journal of Ambient Computing and Intelligence 8, no. 1 (2017): 98–118. http://dx.doi.org/10.4018/ijaci.2017010105.

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In this paper, a new real-time approach for audio recognition of waterbird species in noisy environments, based on a Texas Instruments DSP, i.e. TMS320C6713 is proposed. For noise estimation in noisy water bird's sound, a tonal region detector (TRD) using a sigmoid function is introduced. This method offers flexibility since the slope and the mean of the sigmoid function can be adapted autonomously for a better trade-off between noise overvaluation and undervaluation. Then, the features Mel Frequency Cepstral Coefficients post processed by Spectral Subtraction (MFCC-SS) were extracted for clas

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5

Kumar Singh, Arbind, S. Shivashankar, and S. Janarthanan. "Robust Speech Recognition System for Avionics." Journal of Aerospace Sciences and Technologies, August 14, 2023, 47–54. http://dx.doi.org/10.61653/joast.v56i1.2004.834.

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An isolated Spoken word Recognition system "SRIJAN" (srujan) has been developed by Aeronautical Development Establishment (ADE) This speaker dependent and robust, system employs energy based end point detection, Linear Predictive Code (LPC) coefficients derived cepstral coefficients as feature vectors and Dynamic Time Warping (DTW) algorithm. The DTW algorithm offers belter system performance by minimizing the effect of speaking rate variation. The optimum end point pair (start and end) obtained by taking the average of different end point pairs, resulting from the marginal variation of the lo

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6

Farahani, Gholamreza. "Autocorrelation-based noise subtraction method with smoothing, overestimation, energy, and cepstral mean and variance normalization for noisy speech recognition." EURASIP Journal on Audio, Speech, and Music Processing 2017, no. 1 (2017). http://dx.doi.org/10.1186/s13636-017-0110-8.

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7

К., R. Aida–Zade, Ardil C., and S. Rustamov S. "Investigation of Combined use of MFCC and LPC Features in Speech Recognition Systems." November 2, 2017. https://doi.org/10.5281/zenodo.1133001.

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Statement of the automatic speech recognition problem, the assignment of speech recognition and the application fields are shown in the paper. At the same time as Azerbaijan speech, the establishment principles of speech recognition system and the problems arising in the system are investigated. The computing algorithms of speech features, being the main part of speech recognition system, are analyzed. From this point of view, the determination algorithms of Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictive Coding (LPC) coefficients expressing the basic speech features are devel

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8

К., R. Aida–Zade, Ardil C., and S. Rustamov S. "Investigation of Combined use of MFCC and LPC Features in Speech Recognition Systems." International Journal of Information, Control and Computer Sciences 0.0, no. 8 (2017). https://doi.org/10.5281/zenodo.1314791.

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Abstract:

Statement of the automatic speech recognition problem, the assignment of speech recognition and the application fields are shown in the paper. At the same time as Azerbaijan speech, the establishment principles of speech recognition system and the problems arising in the system are investigated. The computing algorithms of speech features, being the main part of speech recognition system, are analyzed. From this point of view, the determination algorithms of Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictive Coding (LPC) coefficients expressing the basic speech features are devel

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Dissertations / Theses on the topic "Cepstral Mean Subtraction"

1

Neville, Katrina Lee, and katrina neville@rmit edu au. "Channel Compensation for Speaker Recognition Systems." RMIT University. Electrical and Computer Engineering, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080514.093453.

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This thesis attempts to address the problem of how best to remedy different types of channel distortions on speech when that speech is to be used in automatic speaker recognition and verification systems. Automatic speaker recognition is when a person's voice is analysed by a machine and the person's identity is worked out by the comparison of speech features to a known set of speech features. Automatic speaker verification is when a person claims an identity and the machine determines if that claimed identity is correct or whether that person is an impostor. Channel distortion occurs wh

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Book chapters on the topic "Cepstral Mean Subtraction"

1

Boulmaiz, Amira, Djemil Messadeg, Noureddine Doghmane, and Abdelmalik Taleb-Ahmed. "Design and Implementation of a Robust Acoustic Recognition System for Waterbird Species Using TMS320C6713 DSK." In Sensor Technology. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2454-1.ch038.

Full text

Abstract:

In this paper, a new real-time approach for audio recognition of waterbird species in noisy environments, based on a Texas Instruments DSP, i.e. TMS320C6713 is proposed. For noise estimation in noisy water bird's sound, a tonal region detector (TRD) using a sigmoid function is introduced. This method offers flexibility since the slope and the mean of the sigmoid function can be adapted autonomously for a better trade-off between noise overvaluation and undervaluation. Then, the features Mel Frequency Cepstral Coefficients post processed by Spectral Subtraction (MFCC-SS) were extracted for clas

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Conference papers on the topic "Cepstral Mean Subtraction"

1

Naik, Devang K., and Richard J. Mammone. "Channel normalization using pole-filtered cepstral mean subtraction." In SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, edited by Richard J. Mammone and J. David Murley, Jr. SPIE, 1994. http://dx.doi.org/10.1117/12.191872.

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2

Radadia, Purushotam G., and Hemant A. Patil. "A Cepstral Mean Subtraction based features for Singer Identification." In 2014 International Conference on Asian Language Processing (IALP). IEEE, 2014. http://dx.doi.org/10.1109/ialp.2014.6973510.

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3

Du, Feifei, Qizhi Huang, Chengyuan Wei, and Bo Wang. "Speech Endpoint Detection Based on Improved Cepstral Mean Subtraction." In 2012 Second International Conference on Intelligent System Design and Engineering Application (ISDEA). IEEE, 2012. http://dx.doi.org/10.1109/isdea.2012.521.

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