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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 ...
Zhenkun Li, Weiwei Lin, Youqi Zhang
exaly +2 more sources
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 J Povinelli, Michael T Johnson
exaly +3 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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Audio Detection using Mel-frequency Cepstral Coefficients
2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2021The lack of benchmark findings for comparison with any suggested approach is one of the most fundamental challenges in sound event detection research. Distinct research explore different sets of events and datasets, making it difficult to distinguish between new and existing methods.
Uppu Jithendra +2 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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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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Mel-frequency cepstral coefficient analysis in speech recognition
2006 International Conference on Computing & Informatics, 2006Speech recognition is a major topic in speech signal processing. Speech recognition is considered as one of the most popular and reliable biometric technologies used in automatic personal identification systems. Speech recognition systems are used for variety of applications such as multimedia browsing tool, access centre, security and finance.
Chin Kim On +3 more
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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), 2018Audio 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 +5 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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