Results 201 to 210 of about 3,633,480 (246)
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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, 2017In 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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Mel Frequency Cepstral Coefficients and Support Vector Machines for Cough Detection
Lecture Notes in Computer Science, 2023Dustin van der Haar, Mpho Mashika
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Measurement science and technology, 2023
In the real-time test fault diagnosis algorithm based on deep learning, it is difficult to guarantee that the training and testing data come from the same time series distribution.
Yunji Zhao +3 more
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In the real-time test fault diagnosis algorithm based on deep learning, it is difficult to guarantee that the training and testing data come from the same time series distribution.
Yunji Zhao +3 more
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Applied Optics, 2022
To improve the accuracy of signal recognition in optical fiber perimeter defense systems, a method based on Mel frequency cepstral coefficients (MFCCs) and a fast dynamic time warping (FastDTW) algorithm is proposed.
Hainan Lu +3 more
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To improve the accuracy of signal recognition in optical fiber perimeter defense systems, a method based on Mel frequency cepstral coefficients (MFCCs) and a fast dynamic time warping (FastDTW) algorithm is proposed.
Hainan Lu +3 more
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Infrared physics & technology, 2021
Experimentation and analysis of Functional near-infrared spectroscopy (fNIRS) in Brain-Computer Interface (BCI) has increasingly been studied as a communication possibility for patients who are severely paralyzed. This study has applied this technique to
Muhammad Saad Bin Abdul Ghaffar +7 more
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Experimentation and analysis of Functional near-infrared spectroscopy (fNIRS) in Brain-Computer Interface (BCI) has increasingly been studied as a communication possibility for patients who are severely paralyzed. This study has applied this technique to
Muhammad Saad Bin Abdul Ghaffar +7 more
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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 ...
Richard Povinelli, Michael T Johnson
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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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Ensemble Learners for Identification of Spoken Languages using Mel Frequency Cepstral Coefficients
2nd International Conference on Data, Engineering and Applications (IDEA), 2020The most common issue in translating spoken sentences into text is first to accurately identify the speaker's language. Automated speaker language identification is useful in many applications, such as international call centers.
Dilip Singh Sisodia +3 more
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