Feature extraction using Spectral Centroid and Mel Frequency Cepstral Coefficient for Quranic Accent Automatic Identification
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Shaiful Jahari Hashim | Noraziahtulhidayu Kamarudin | Mohammad Ali Nematollahi | S. A. R. Al-Haddad | Abd Rauf Bin Hassan
[1] Dick Blandford,et al. Introduction to Digital Signal Processing , 2012 .
[2] Ia Musa. Remediating deficiencies in the implementation of the rules of ‘ Ilmuttajwid and ‘ Ilmul-Qira’at in Nigeria. , 2011 .
[3] Tien Ping Tan,et al. Analysis of Malay Speech Recognition for Different Speaker Origins , 2012, 2012 International Conference on Asian Language Processing.
[4] W. El Falou,et al. Analysis and implementation of a "Quranic" verses delimitation system in audio files using speech recognition techniques , 2006, 2006 2nd International Conference on Information & Communication Technologies.
[5] Vidhyasaharan Sethu,et al. Investigation of spectral centroid features for cognitive load classification , 2011, Speech Commun..
[6] Heiga Zen,et al. On the Use of Kernel PCA for Feature Extraction in Speech Recognition , 2003, IEICE Trans. Inf. Syst..
[7] Danoush Hosseinzadeh,et al. Combining Vocal Source and MFCC Features for Enhanced Speaker Recognition Performance Using GMMs , 2007, 2007 IEEE 9th Workshop on Multimedia Signal Processing.
[8] Beth Logan,et al. Mel Frequency Cepstral Coefficients for Music Modeling , 2000, ISMIR.
[9] Chang-Hsing Lee,et al. Music genre classification using modulation spectral features and multiple prototype vectors representation , 2011, 2011 4th International Congress on Image and Signal Processing.
[10] A. M. Natarajan,et al. A Robust Front-End Processor combining Mel Frequency Cepstral Coefficient and Sub-band Spectral Centroid Histogram methods for Automatic Speech Recognition , 2009 .
[11] Perry R. Cook,et al. Towards Automatic Musical Instrument Timbre Recognition , 2010 .
[12] Emanuele Pollastri,et al. Musical Instrument Timbres Classification with Spectral Features , 2001, 2001 IEEE Fourth Workshop on Multimedia Signal Processing (Cat. No.01TH8564).
[13] M. O'Farrell,et al. Musical instrument identification using Principal Component Analysis and Multi-Layered Perceptrons , 2008, 2008 International Conference on Audio, Language and Image Processing.
[14] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[15] Ana María Martínez Enríquez,et al. Voice Content Matching System for Quran Readers , 2010, 2010 Ninth Mexican International Conference on Artificial Intelligence.
[16] Tae Hong Park. Introduction to digital signal processing - Computer Musically Speaking , 2009 .
[17] Noor Jamaliah Ibrahim. Automated TAJWEED checking rules engine for Quranic verse recitation , 2010 .
[18] A. Zabidi,et al. Pattern classification in recognizing Qalqalah Kubra pronuncation using multilayer perceptrons , 2012, 2012 International Symposium on Computer Applications and Industrial Electronics (ISCAIE).
[19] M. H. Purnomo,et al. FFT-based features selection for Javanese music note and instrument identification using support vector machines , 2012, 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE).
[20] Θεόδωρος Γιαννακόπουλος,et al. Study and application of acoustic information for the detection of harmful content and fusion with visual information , 2009 .
[21] Rubita Sudirman,et al. Difficulties of Standard Arabic Phonemes Spoken by Non-Arab Primary School Children based on Formant Frequencies , 2011 .
[22] Kuldip K. Paliwal,et al. Robust speech recognition in noisy environments based on subband spectral centroid histograms , 2006, IEEE Transactions on Audio, Speech, and Language Processing.
[23] Samir A. Elsagheer Mohamed,et al. Virtual Learning System (Miqra’ah) for Quran Recitations for Sighted and Blind Students , 2014 .
[24] John Backus,et al. Input impedance curves for the brass instruments , 1976 .
[25] Roman Kuc,et al. Introduction to Digital Signal Processing , 2021, Digital Signal Processing.
[26] Wasfi G. Al-Khatib,et al. Identification of Question and Non-Question Segments in Arabic Monologue Based on Prosodic Features Using Type-2 Fuzzy Logic Systems , 2010, 2010 Second International Conference on Computational Intelligence, Modelling and Simulation.