Results 181 to 190 of about 6,219 (212)

RETRACTED: Breathing site classification via joint mel frequency cepstral coefficients and gammatone frequency cepstral coefficients approach

Journal of Intelligent & Fuzzy Systems
This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Zhang, Jiarui, Ling, Bingo Wing-Kuen
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Encrypted Domain Mel-Frequency Cepstral Coefficient and Fragile Audio Watermarking

2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), 2018
Audio has become increasingly important in modern social communication and mobile Internet, e.g., the employment of voice messaging in mobile social Apps. In the scenario of cloud computing, we need to consider the privacy protection of the audio content and the integrity of the audio simultaneously.
Jian Chen, Ziyang Chen, Peijia Zheng, Jianting Guo, Wei Zhang 0016, Jiwu Huang   +5 more
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Mel-Frequency Cepstral and Linear Predictive Coefficients

2018
Mel-frequency cepstral coefficients (MFCCs) and linear predictive coefficients (LPCs) are features used to describe sound according to time, frequency, and amplitude. These techniques, which are mainly used in speech analysis, are reviewed step by step for a good understanding and practice.
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Identification of satellite images based on mel frequency cepstral coefficients

2009 International Conference on Computer Engineering & Systems, 2009
MFCC technique is an efficient technique which can be used for speech signals' classification as MFCC can be applied for 1-D signals. This paper suggests a new application for MFCC technique as it can be used for classification of satellite images, which are 2-D objects.
T. M. Talal, Ayman El-Sayed
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Extraction of speech signal based on Power Normalized Cepstral Coefficient and Mel Frequency Cepstral Coefficient: A comparison

2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016
Speech processing is emerged as one of the important application area of digital signal processing. Power Normalized Cepstral Coefficients (PNCC) and Mel Frequency Cepstral Coefficient (MFCC) are mainly used in feature extraction of speech signals.
null Bharathi, Narain Ponraj, Merlin Mercy   +2 more
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On the inversion of Mel-frequency cepstral coefficients for speech enhancement applications

2008 International Conference on Signals and Electronic Systems, 2008
The use of Mel-frequency cepstral coefficients (MFCCs) is well established in the fields of speech processing, particularly for speaker modeling within a Gaussian mixture model (GMM) speaker recognition system. The use of GMMs for speech enhancement applications has only recently been proposed in the literature; the concept of direct inversion of the ...
Laura E. Boucheron, Phillip L. De Leon
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Mel-frequency cepstral coefficients as features for automatic speaker recognition

2015 23rd Telecommunications Forum Telfor (TELFOR), 2015
Automatic speaker recognizer can be based on the use of mel-frequency cepstral coefficients as speaker features. Mel-frequency cepstral coefficients depend on energy inside considered auditory critical bands. These auditory critical bands model masking phenomena.
Ivan D. Jokic, Stevan D. Jokic, Vlado D. Delic, Zoran H. Perie   +3 more
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Mel Frequency Cepstral Coefficients Based Similar Albanian Phonemes Recognition

2016
In Albanian language there are several phonemes that are similar in pronunciation like /q/ - /c/, /rr/ - /r/, /th/ - /dh/ and /gj/ - /xh/. These phonemes are difficult to distinguish by human ear even for native speaking Albanians from different regions.
Bertan Karahoda, Krenare Pireva, Ali Shariq Imran   +2 more
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Multiple time resolutions for derivatives of Mel-frequency cepstral coefficients

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01., 2005
Most speech recognition systems are based on Mel-frequency cepstral coefficients and their first- and second-order derivatives. The derivatives are normally approximated by fitting a linear regression line to a fixed-length segment of consecutive frames. The time resolution and smoothness of the estimated derivative depends on the length of the segment.
G. Stemmer, C. Hacker, E. Noth, H. Niemann   +3 more
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Phase Based Mel Frequency Cepstral Coefficients for Speaker Identification

2016
In this paper new Phase based Mel frequency Cepstral Coefficient (PMFCC) are used for speaker identification. GMM with VQ are used as a classifier for classification of speakers. The identification performance of proposed features is compared with identification performance of MFCC features and phase features. The performance of PMFCC features has been
Sumit Srivastava, Mahesh Chandra, G. Sahoo   +2 more
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