Results 121 to 130 of about 600 (157)
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Behavior Anomaly Detection Fused with Features of Mel Frequency Cepstrum Coefficients
2020 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), 2020In recent years, with the rise of artificial intelligence, the research in the field of pattern recognition is developing rapidly. Its supporting algorithms mainly include neural network and support vector machine (SVM), which are widely used in various fields such as industrial detection, aviation, medical treatment, finance, internet and so on.
Fuyong Lyu +5 more
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Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489), 2002
The speech parametrization methods: linear prediction cepstrum coefficients and mel-frequency cepstrum coefficients were compared with regard to language identification accuracy in a Gaussian mixture model based language identification system. Ten different languages were used to test against a set of ten second test files.
Wong, Eddie, Sridharan, Sridha
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The speech parametrization methods: linear prediction cepstrum coefficients and mel-frequency cepstrum coefficients were compared with regard to language identification accuracy in a Gaussian mixture model based language identification system. Ten different languages were used to test against a set of ten second test files.
Wong, Eddie, Sridharan, Sridha
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The fixed-point optimization of mel frequency cepstrum coefficients for speech recognition
Proceedings of 2011 6th International Forum on Strategic Technology, 2011Speech recognition is a computationally complexity process and it is suitable for battery powered devices like mobile phones and other personal PDAs. Particularly the parts of mel-scaled frequency cepstrum coefficients (MFCCs) are a process of dimension reduction for reducing resources to accurately describe speech samples.
null Ge Zhang +3 more
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Vision Transformer for Music Genre Classification using Mel-frequency Cepstrum Coefficient
2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON), 2021The music industry has gone through some seismic changes since the dawn of the Internet. It has been reaching a much larger audience because the appetite for different music styles has increased. New songs are written and released every day, which makes genre classification a tiresome and lengthy task.
Yash Khasgiwala, Jash Tailor
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Multimedia Tools and Applications, 2021
A significant role is played by Speech Emotion Recognition (SER) with different applications in affective computing and human-computer interface. In literature, the most adapted technique for recognition of emotion was based on simple feature extraction using a simple classifier.
Manju D. Pawar, Rajendra D. Kokate
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A significant role is played by Speech Emotion Recognition (SER) with different applications in affective computing and human-computer interface. In literature, the most adapted technique for recognition of emotion was based on simple feature extraction using a simple classifier.
Manju D. Pawar, Rajendra D. Kokate
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Calculation of LPC-based cepstrum coefficients using mel-scale frequency warping
COMSIG 1991 Proceedings: South African Symposium on Communications and Signal Processing, 2002This paper describes a method for warping the frequency axis of cepstrum coefficients in a way analogous to the preprocessing performed by the human ear. The equations are derived and historical background relating to different warping scales is discussed.
C.J. van der Merwe, J.A. du Preez
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Speaker recognition using mel-frequency cepstrum coefficients and sum square error
2017 3rd International Conference on Wireless and Telematics (ICWT), 2017The Method of Mel-Frequency Cepstral Coefficients Vector Quantization (MFCC-VQ) can be used in the speaker verification system. The process of feature extraction of speech signal using Mel Frequency Cepstral Coefficients (MFCC) vectors will produce acoustic speech signal.
Atik Charisma +2 more
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Algorithm for Gunshot Detection Using Mel-Frequency Cepstrum Coefficients (MFCC)
2014Protection of forests and wildlife needs efficient, reliable, and real-time detection of events such as gunshots, wood cutting, distress call of animals, etc. In this paper, we propose a gunshot detection technique through acoustic signal pattern recognition utilizing Mel-Frequency Cepstrum Coefficients (MFCC). In this work, MFCC is used to extract the
Preetam Suman +3 more
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Detection of possibility of Laryngeal Cancer through Mel Frequency Cepstrum Coefficient Analysis
2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), 2018Laryngeal Cancer is a condition in which cancerous cells are formed in larynx. Notable symptoms are hoarseness in the voice, sore throat, trouble or pain while swallowing and ear pain. The detection of the modification in voice through Acoustic analysis can serve as a complement to other medical procedures.
S Kavya, Raghuram Shivram
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Filled Pause Classification Using Energy-Boosted Mel-Frequency Cepstrum Coefficients
2014Filled pause is one type of disfluency, identified as the often occurred disfluency in spontaneous speech and known to affect Automatic Speech Recognition accuracy. The purpose of this study is to analyze the impact of boosting Mel-Frequency Cepstral Coefficients with energy feature in classifying filled pause. A total of 828 filled pauses comprising a
Raseeda Hamzah +2 more
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