Oriented and Interpolated Local Features for Speech Recognition of Vocal Fold Disordered Patients

Zulfiqar Ali; Ghulam Muhammad; Mansour  Alsulaiman; Irraivan Elamvazuthi; Khalid Al-Mutib

Oriented and Interpolated Local Features for Speech Recognition of Vocal Fold Disordered Patients

Zulfiqar Ali, Ghulam Muhammad, Mansour Alsulaiman, Irraivan Elamvazuthi, Khalid Al-Mutib

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Abstract

A novel technique of oriented local features (OLF) for speech recognition has been introduced in this paper. A speech recognition system for dysphonic patients is implemented by application of the proposed technique. The developed system is evaluated by performing the training in three different ways: (a) with pathological samples, (b) with normal samples, and (c) with pathological and normal samples together. We compare the performance of the proposed feature with the most widely used speech feature in speech recognition, i.e., Mel-frequency cepstral coefficients. The Hidden Markov model is used for recognizing the speech. The proposed technique achieved a 94.98% recognition rate, which is almost identical to the recognition rate of 95.45% obtained with MFCC.

Original language	English
Pages (from-to)	1-11
Number of pages	9
Journal	International Journal for Computers and Their Applications
Volume	22
Issue number	1
Publication status	Published (in print/issue) - 31 Mar 2015

Keywords

Vocal fold disorders
Automatic speech recognition
Arabic digits
MFCC
HMM

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title = "Oriented and Interpolated Local Features for Speech Recognition of Vocal Fold Disordered Patients",

abstract = "A novel technique of oriented local features (OLF) for speech recognition has been introduced in this paper. A speech recognition system for dysphonic patients is implemented by application of the proposed technique. The developed system is evaluated by performing the training in three different ways: (a) with pathological samples, (b) with normal samples, and (c) with pathological and normal samples together. We compare the performance of the proposed feature with the most widely used speech feature in speech recognition, i.e., Mel-frequency cepstral coefficients. The Hidden Markov model is used for recognizing the speech. The proposed technique achieved a 94.98% recognition rate, which is almost identical to the recognition rate of 95.45% obtained with MFCC.",

keywords = "Vocal fold disorders, Automatic speech recognition, Arabic digits, MFCC, HMM",

author = "Zulfiqar Ali and Ghulam Muhammad and Mansour Alsulaiman and Irraivan Elamvazuthi and Khalid Al-Mutib",

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T1 - Oriented and Interpolated Local Features for Speech Recognition of Vocal Fold Disordered Patients

AU - Ali, Zulfiqar

AU - Muhammad, Ghulam

AU - Alsulaiman, Mansour

AU - Elamvazuthi, Irraivan

AU - Al-Mutib, Khalid

PY - 2015/3/31

Y1 - 2015/3/31

N2 - A novel technique of oriented local features (OLF) for speech recognition has been introduced in this paper. A speech recognition system for dysphonic patients is implemented by application of the proposed technique. The developed system is evaluated by performing the training in three different ways: (a) with pathological samples, (b) with normal samples, and (c) with pathological and normal samples together. We compare the performance of the proposed feature with the most widely used speech feature in speech recognition, i.e., Mel-frequency cepstral coefficients. The Hidden Markov model is used for recognizing the speech. The proposed technique achieved a 94.98% recognition rate, which is almost identical to the recognition rate of 95.45% obtained with MFCC.

AB - A novel technique of oriented local features (OLF) for speech recognition has been introduced in this paper. A speech recognition system for dysphonic patients is implemented by application of the proposed technique. The developed system is evaluated by performing the training in three different ways: (a) with pathological samples, (b) with normal samples, and (c) with pathological and normal samples together. We compare the performance of the proposed feature with the most widely used speech feature in speech recognition, i.e., Mel-frequency cepstral coefficients. The Hidden Markov model is used for recognizing the speech. The proposed technique achieved a 94.98% recognition rate, which is almost identical to the recognition rate of 95.45% obtained with MFCC.

KW - Vocal fold disorders

KW - Automatic speech recognition

KW - Arabic digits

KW - MFCC

KW - HMM

M3 - Article

SN - 1076-5204

VL - 22

SP - 1

EP - 11

JO - International Journal for Computers and Their Applications

JF - International Journal for Computers and Their Applications

IS - 1

ER -

Oriented and Interpolated Local Features for Speech Recognition of Vocal Fold Disordered Patients

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Keywords

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