Results 211 to 220 of about 3,633,480 (246)

Analysis of Asthma by using Mel frequency cepstral coefficient

2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), 2016
Asthma 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
openaire   +1 more source

Emotions Understanding Model from Spoken Language using Deep Neural Networks and Mel-Frequency Cepstral Coefficients

IEEE Conference on Evolving and Adaptive Intelligent Systems, 2020
The ability to understand people through spoken language is a skill that many human beings take for granted. On the contrary, the same task is not as easy for machines, as consequences of a large number of variables which vary the speaking sound wave ...
Marco Giuseppe de Pinto, Marco Polignano, P. Lops, G. Semeraro   +3 more
semanticscholar   +1 more source

Mel-frequency cepstral coefficient analysis in speech recognition

2006 International Conference on Computing & Informatics, 2006
Speech 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, Paulraj M. Pandiyan, Sazali Yaacob, Azali Saudi   +3 more
openaire   +1 more source

Heartbeat sound classification using Mel-frequency cepstral coefficients and deep convolutional neural network

Advances in Computational Techniques for Biomedical Image Analysis, 2020
One of the main sources of death in this world is cardiovascular disorders. The timely recognition is significant to monitor heart health. The auscultation of the human heart is an essential technique in medical practices since it is simple, reliable ...
Shamik Tiwari, Varun Sapra, Anurag Jain
semanticscholar   +1 more source

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), 2018
Audio 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, Ziyang Chen, Peijia Zheng, Jianting Guo, Wei Zhang 0016, Jiwu Huang   +5 more
openaire   +2 more sources

Extracting Mel-Frequency and Bark-Frequency Cepstral Coefficients from Encrypted Signals

Interspeech, 2019
We describe a method for extracting Mel-Frequency and BarkFrequency Cepstral Coefficient from an encrypted signal without having to decrypt any intermediate values.
Patricia Thaine, Gerald Penn
semanticscholar   +1 more source

Identification of satellite images based on mel frequency cepstral coefficients

2009 International Conference on Computer Engineering & Systems, 2009
MFCC technique is an efficient technique which can be used for speech signals' classification as MFCC can be applied for 1-D signals. This paper suggests a new application for MFCC technique as it can be used for classification of satellite images, which are 2-D objects.
T. M. Talal, Ayman El-Sayed
openaire   +1 more source

Extraction of speech signal based on Power Normalized Cepstral Coefficient and Mel Frequency Cepstral Coefficient: A comparison

2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016
Speech processing is emerged as one of the important application area of digital signal processing. Power Normalized Cepstral Coefficients (PNCC) and Mel Frequency Cepstral Coefficient (MFCC) are mainly used in feature extraction of speech signals.
null Bharathi, Narain Ponraj, Merlin Mercy   +2 more
openaire   +1 more source

Mel-Frequency Cepstral and Linear Predictive Coefficients

2018
Mel-frequency cepstral coefficients (MFCCs) and linear predictive coefficients (LPCs) are features used to describe sound according to time, frequency, and amplitude. These techniques, which are mainly used in speech analysis, are reviewed step by step for a good understanding and practice.
openaire   +1 more source

Leak Detection in Water Distribution Pipes Based on CNN with Mel Frequency Cepstral Coefficients

International Conferences on Innovation in Artificial Intelligence, 2019
The acoustic signals collected by a listening device on pipelines are often utilized for detecting leakage in buried water pipelines. In practice, the operator carries with a listening device to collect the acoustic signal on the road along the direction
W. Chuang, Y. Tsai, Li-Hua Wang
semanticscholar   +1 more source