Results 121 to 130 of about 3,790,103 (166)
MEL-FREQUENCY CEPSTRAL COEFFICIENTS FOR SPEAKER RECOGNITION : A REVIEW
International Journal of Advance Engineering and Research Development, 2015 openaire +1 more source
Speaker Recognition Using Mel-Frequency Cepstral Coefficient Distributions
Izvestiya of Altai State University, 2014 Alexey Zakovryashin +2 more
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2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 2018 In this paper a comparative between Mel Frequency Cepstral Coefficients (MFCC) and Inverse Mel Frequency Cepstral Coefficients (IMFCC) features for an automatic bird species recognition system is proposed with the aim to validate IMFCC as a feature that can also be extracted for bird species recognition.
Aldonso Becerra
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Mel-frequency Cepstral Coefficients for Eye Movement Identification
2012 IEEE 24th International Conference on Tools with Artificial Intelligence, 2012 Human identification is an important task for various activities in society. In this paper, we consider the problem of human identification using eye movement information. This problem, which is usually called the eye movement identification problem, can be solved by training a multiclass classification model to predict a person's identity from his or ...
Viet Cuong Nguyen +2 more
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Structural Health Monitoring, 2023 Bridge damage detection using vibration data has been confirmed as a promising approach. Compared to the traditional method that typically needs to install sensors or systems directly on bridges, the drive-by bridge damage detection method has gained ...
Weiwei Lin, Zhenkun Li, Youqi Zhang
exaly +2 more sources
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Computing Mel-frequency cepstral coefficients on the power spectrum
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002We present a method to derive Mel-frequency cepstral coefficients directly from the power spectrum of a speech signal. We show that omitting the filterbank in signal analysis does not affect the word error rate. The presented approach simplifies the speech recognizers front end by merging subsequent signal analysis steps into a single one.
Sirko Molau +3 more
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Chip design of mel frequency cepstral coefficients for speech recognition
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002The mel frequency cepstral coefficients (MFCC) is one of the mast important features, which is required among various kinds of speech applications. The chip for speech features extraction based on the MFCC algorithm is first proposed. The chip is designed with area efficient consideration and can achieve the following: (1) the reduction of table size ...
Jia-Ching Wang +2 more
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Minimum Mean-Squared Error Estimation of Mel-Frequency Cepstral Coefficients Using a Novel Distortion Model [PDF]
IEEE Transactions on Audio Speech and Language Processing, 2008 In this paper, a new method for statistical estimation of Mel-frequency cepstral coefficients (MFCCs) in noisy speech signals is proposed. Previous research has shown that model-based feature domain enhancement of speech signals for use in robust speech ...
Michael Johnson +2 more
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Fingerprint recognition using mel-frequency cepstral coefficients
Pattern Recognition and Image Analysis, 2010This paper presents a new fingerprint recognition method based on mel-frequency cepstral coefficients (MFCCs). In this method, cepstral features are extracted from a group of fingerprint images, which are transformed first to 1-D signals by lexicographic ordering.
F. G. Hashad +4 more
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Analysis of Asthma by using Mel frequency cepstral coefficient
2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), 2016Asthma is a lung disease that affects airflow to and From the lungs. A whistling sound comes when a person suffering from asthma breathes in and out. Major symptoms of asthma are chest stiffness, breathe shortness and cough production during night and morning.
V. D. Dighore, V. R. Thool
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