Cover Image

MFCC in audio signal processing for voice disorder: a review

Voice Disorder or Dysphonia has caught the attention of audio signal process engineers and researchers. The efficiency of several feature extraction and classifier implementation techniques in identifying voice abnormalities has been investigated. Mel-Frequency Cepstral Coefficient (MFCC) has been e...

Full description

Saved in:

Bibliographic Details
Main Authors:	Sidhu M.S., Latib N.A.A., Sidhu K.K.
Other Authors:	56259597000
Format:	Article
Published:	Springer 2025
Subjects:	Classification (of information) Decision trees Extraction Feature extraction Neural networks Speech communication Speech recognition Audio signal Feature classifiers Feature extractor Features extraction Implementation techniques Mel frequency cepstral co-efficient Mel-frequency cepstral coefficients Support vectors machine Voice disorders Support vector machines
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Understanding the Use of Acoustic Measurement and Mel Frequency Cepstral Coefficient (MFCC) Features for the Classification of Depression Speech
by: Shanmugam M., et al.
Published: (2024)

Comparison of speech parameterization techniques for the classification of speech disfluencies
by: Chong, Yen Fook, et al.
Published: (2014)

Speech recognition using MFCC and DTW classifier
by: Mukrimah, Nawir
Published: (2016)

A hybrid expert system approach for telemonitoring of vocal fold pathology
by: Hariharan, Muthusamy, Dr., et al.
Published: (2014)

Feature based classification for classroom speech intelligibility prediction
by: M. Ridhwan, Tamjis, et al.
Published: (2014)

Simulink model of Mel Frequency Cepstral Coefficient analysis for extracting asphyxiated infant cry features
by: Mohebbi Zulfikar, Mohd Ali, et al.
Published: (2012)

Automated system for stress evaluation based on EEG signal: A prospective review
by: Saidatul Ardeenawatie, Awang, et al.
Published: (2011)

Iris recognition system by using support vector machines
by: Hasimah, Ali, et al.
Published: (2009)

An accurate infant cry classification system based on continuos hidden Markov model
by: Abdulaziz Y., et al.
Published: (2023)

Malay speech recognition in normal and noise condition
by: Fook, C. Y., et al.
Published: (2013)

Moving vehicle noise classification using backpropagation algorithm
by: Norasmadi, Abdul Rahim, et al.
Published: (2011)

Face recognition using eigenfaces and neural networks
by: Mohamed Rizon, et al.
Published: (2011)

Face recognition using eigenfaces and neural networks
by: Mohamed Rizon, et al.
Published: (2011)

A new hybrid intelligent system for accurate detection of Parkinson's disease
by: Hariharan, Muthusamy, et al.
Published: (2014)

Feature space reduction in ethnically diverse Malaysian English accents classification
by: Yusnita, Mohd Ali, et al.
Published: (2014)

Human activities classification based on ?-OTDR system by utilizing gammatone filter cepstrum coefficient envelope using support vector machine
by: Saleh N.L., et al.
Published: (2024)

Feature extraction for biometric recognition with photoplethysmography signals
by: Resit Kavsaoglu, A., et al.
Published: (2014)

Electroencephalogram (EEG)-based systems to monitor driver fatigue: a review
by: Seri Rahayu, Kamat, et al.
Published: (2022)

Infant cry recognition system: A comparison of system performance based on Mel frequency and linear prediction cepstral coefficients
by: Abdulaziz Y., et al.
Published: (2023)

Analysis of Low and High Level Feature Extraction in Human Movement
by: Norazlin Ibrahim, Norsehah Abd Karim, et al.
Published: (2013)

Application of feedforward neural network for the classification of pathological voices
by: Sazali, Yaacob, Prof. Dr., et al.
Published: (2011)

A review: Malay speech recognition and audio visual speech recognition
by: C., Y. Fook, et al.
Published: (2012)

Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment
by: Kyaw M.M., et al.
Published: (2023)

A Hybrid Cracked Tiers Detection System Based on Adaptive Correlation Features Selection and Deep Belief Neural Networks
by: Al-juboori A.M., et al.
Published: (2024)

E-mail classifications using Support Vector machine
by: Ali, Selamat, et al.
Published: (2009)

Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor
by: Thulfiqar Hussein, Mandeel, et al.
Published: (2019)

DWT and MFCC based human emotional speech classification using LDA
by: Murugappan, Muthusamy, Dr., et al.
Published: (2012)

Classification of fruits using Probabilistic Neural Networks - Improvement using color features
by: Mustafa N.B.A., et al.
Published: (2023)

Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network
by: Hariharan, Muthusamy, et al.
Published: (2011)

Analysis of partial discharge measurement data using a support vector machine
by: Aziz N.F.A., et al.
Published: (2023)

Malaysian license plate recognition system
by: Siti Marhainis, Othman, et al.
Published: (2012)

Detection of acute leukaemia cells using variety of features and neural networks
by: A. S., Abdul Nasir, et al.
Published: (2011)

A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers
by: Ahmed I.T., et al.
Published: (2025)

MFCC based recognition of repetitions and prolongations in stuttered speech using k-NN and LDA
by: Lim, Sin Chee, et al.
Published: (2010)

Machine learning approach for sudden cardiac arrest prediction based on optimal heart rate variability features
by: Murukesan, L., et al.
Published: (2015)

Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks
by: Hema, Chengalvarayan Radhakrishnamurthy, et al.
Published: (2009)

Discrimination of vision impairments using single trial VEPs
by: Vijean, Vikneswaran, et al.
Published: (2014)

Evaluating endpoint detection algorithms for isolated word from Malay parliamentary speech
by: Seman N., et al.
Published: (2023)

Classification of speech dysfluencies with MFCC and LPCC features
by: Ooi, Chia Ai, et al.
Published: (2011)

Supervised neural network classifier for voice pathology
by: Murugesa Pandiyan, Paulraj, Prof. Madya Dr,, et al.
Published: (2011)