Results 171 to 180 of about 28,361 (199)

Mel-frequency cepstrum encoding in analog floating-gate circuitry

2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353), 2003
This paper presents a continuous-time mel-frequency cepstrum encoding IC using analog circuits and floating-gate computational arrays. We present the dynamics of several floating-gate computational building blocks and accompanying experimental measurements. We also present a novel approach to programmable signal spectrum decomposition, analog frequency
Paul D. Smith, Matt Kucic, Richard Ellis, Paul E. Hasler, David V. Anderson   +4 more
openaire   +1 more source

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

Fingerprint recognition using mel-frequency cepstral coefficients

Pattern Recognition and Image Analysis, 2010
This 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, T. M. Halim, S. M. Diab, B. M. Sallam, F. E. Abd El-Samie   +4 more
openaire   +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

The extraction and simulation of Mel frequency cepstrum speech parameters

2012 International Conference on Systems and Informatics (ICSAI2012), 2012
This paper takes consideration of (voices of) the characteristics of voice processing by the human auditory system, adopts triangle filter to do signal preprocessing, and uses logarithm operations of all filter output for extracting Mel frequency cepstrum Coefficient (MFCC).
Hongyu Xu, Xia Zhang, Liang Jia
openaire   +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   +1 more source

Emotion recognition using Lyapunov exponent of the Mel-frequency energy bands

Proceedings of the 2014 6th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), 2014
This paper presents a method for emotion recognition by using LLE - Largest Lyapunov exponent of the Mel-frequency energy bands for the Romanian language. The emotion recognition for features vectors that contains LLE is better using Support Vector Machine - SVM classifier (76.4%) than Weighted K-Nearest Neighbors - WKNN classifier (72.8%).
Monica Feraru, Marius-Dan Zbancioc
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

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

Emotion recognition from speech signal using mel-frequency cepstral coefficients

2015 9th International Conference on Electrical and Electronics Engineering (ELECO), 2015
In this paper, mel-frequency cepstral coefficients are investigated for emotional content of speech signal. The features are extracted from spoken utterance. When these features are extracted, speech signal is divided small frames and each frame overlap a part of previous frame.
Atasoy, Ayten, KORKMAZ, Onur Erdem
openaire   +2 more sources