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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   +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   +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   +3 more
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Choosing an accurate number of mel frequency cepstral coefficients for audio classification purpose

Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis, 2017
In this paper, we study several audio classification schemes applied on different number of features for multiclass classification with imbalanced datasets. As features, we proposed the liftering Mel frequency cepstral coefficients, while for classification we use probabilistic methods, instance-based learning algorithms, support vector machines ...
Lacrimioara Grama, Corneliu Rusu
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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   +2 more
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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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Speech production based on the mel-frequency cepstral coefficients

6th European Conference on Speech Communication and Technology, 1999
Zbynek Tychtl, Josef Psutka
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Interpreting mel frequency cepstral coefficients for frication on the Turkish rhotic

Canonically, the “r” in Turkish is produced as an alveolar tap; however, word-finally, this tap has been described as devoiced and fricated. Previous work found that mel frequency cepstral coefficients (MFCCs) show spectral differences between canonical and fricated taps in Turkish.
Miklas, Janalyn, Kelley, Matthew C.
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