Driver behavior state recognition based on silence removal speech

Driver behavior state recognition based on silence removal speech

Numerous researches have linked driver behavior to the cause of accident and some studies are concentrated into different input providing practical preventive measures. Nonetheless speech has been found to be a suitable input source in understanding and analyzing driver’s behavior state due to the...

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Main Authors: Kamaruddin, Norhaslinda, Abdul Rahman, Abdul Wahab, Mohamad Halim, Khairul Ikhwan, Mohd Noh, Muhammad Hafiq Iqma
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2017
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://irep.iium.edu.my/57261/
http://irep.iium.edu.my/57261/
http://irep.iium.edu.my/57261/
http://irep.iium.edu.my/57261/1/52761_Driver%20behavior%20state_complete.pdf
http://irep.iium.edu.my/57261/2/57261_Driver%20behavior%20state_SCOPUS_new.pdf
id iium-57261
recordtype eprints
spelling iium-572612017-06-13T05:39:48Z http://irep.iium.edu.my/57261/ Driver behavior state recognition based on silence removal speech Kamaruddin, Norhaslinda Abdul Rahman, Abdul Wahab Mohamad Halim, Khairul Ikhwan Mohd Noh, Muhammad Hafiq Iqma TJ Mechanical engineering and machinery Numerous researches have linked driver behavior to the cause of accident and some studies are concentrated into different input providing practical preventive measures. Nonetheless speech has been found to be a suitable input source in understanding and analyzing driver’s behavior state due to the underlying emotional information when the driver speaks and such changes can be measured. However, the massive amount of driving speech data may hinder optimal performance of processing and analyzing the data due to the computational complexity and time constraint. This paper presents a silence removal approach using Short Term Energy (STE) and Zero Crossing Rate (ZCR) prior to extracting the relevant features in order to reduce the computational time in a vehicular environment. Mel Frequency Cepstral Coefficient (MFCC) feature extraction method coupled with Multi Layer Perceptron (MLP) classifier are employed to get the driver behavior state recognition performance. Experimental results demonstrated that the proposed approach is able to obtain comparable performance with accuracy ranging between 58.7% and 76.6% to differentiate four driver behavior states, namely; talking through cell telephone phone, out-burst laughing, sleepy and normal driving. It is envisages that such engine can be extended for a more comprehensive driver behavior identification system that may acts as an embedded warning system for sleepy driver. Institute of Electrical and Electronics Engineers Inc. 2017-04-19 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/57261/1/52761_Driver%20behavior%20state_complete.pdf application/pdf en http://irep.iium.edu.my/57261/2/57261_Driver%20behavior%20state_SCOPUS_new.pdf Kamaruddin, Norhaslinda and Abdul Rahman, Abdul Wahab and Mohamad Halim, Khairul Ikhwan and Mohd Noh, Muhammad Hafiq Iqma (2017) Driver behavior state recognition based on silence removal speech. In: 1st International Conference on Informatics and Computing, ICIC 2016, 28-29 October, 2016, Mataram; Indonesi. http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7905713 10.1109/IAC.2016.7905713
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Kamaruddin, Norhaslinda
Abdul Rahman, Abdul Wahab
Mohamad Halim, Khairul Ikhwan
Mohd Noh, Muhammad Hafiq Iqma
Driver behavior state recognition based on silence removal speech
description Numerous researches have linked driver behavior to the cause of accident and some studies are concentrated into different input providing practical preventive measures. Nonetheless speech has been found to be a suitable input source in understanding and analyzing driver’s behavior state due to the underlying emotional information when the driver speaks and such changes can be measured. However, the massive amount of driving speech data may hinder optimal performance of processing and analyzing the data due to the computational complexity and time constraint. This paper presents a silence removal approach using Short Term Energy (STE) and Zero Crossing Rate (ZCR) prior to extracting the relevant features in order to reduce the computational time in a vehicular environment. Mel Frequency Cepstral Coefficient (MFCC) feature extraction method coupled with Multi Layer Perceptron (MLP) classifier are employed to get the driver behavior state recognition performance. Experimental results demonstrated that the proposed approach is able to obtain comparable performance with accuracy ranging between 58.7% and 76.6% to differentiate four driver behavior states, namely; talking through cell telephone phone, out-burst laughing, sleepy and normal driving. It is envisages that such engine can be extended for a more comprehensive driver behavior identification system that may acts as an embedded warning system for sleepy driver.
format Conference or Workshop Item
author Kamaruddin, Norhaslinda
Abdul Rahman, Abdul Wahab
Mohamad Halim, Khairul Ikhwan
Mohd Noh, Muhammad Hafiq Iqma
author_facet Kamaruddin, Norhaslinda
Abdul Rahman, Abdul Wahab
Mohamad Halim, Khairul Ikhwan
Mohd Noh, Muhammad Hafiq Iqma
author_sort Kamaruddin, Norhaslinda
title Driver behavior state recognition based on silence removal speech
title_short Driver behavior state recognition based on silence removal speech
title_full Driver behavior state recognition based on silence removal speech
title_fullStr Driver behavior state recognition based on silence removal speech
title_full_unstemmed Driver behavior state recognition based on silence removal speech
title_sort driver behavior state recognition based on silence removal speech
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2017
url http://irep.iium.edu.my/57261/
http://irep.iium.edu.my/57261/
http://irep.iium.edu.my/57261/
http://irep.iium.edu.my/57261/1/52761_Driver%20behavior%20state_complete.pdf
http://irep.iium.edu.my/57261/2/57261_Driver%20behavior%20state_SCOPUS_new.pdf
first_indexed 2023-09-18T21:20:55Z
last_indexed 2023-09-18T21:20:55Z
_version_ 1777411875326132224

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