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Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction

B Birch, Christian Griffiths, A Morgan

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Volume: 235, Issue: 12, Pages: 1939 - 1948

Swansea University Author: Christian Griffiths

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DOI (Published version): 10.1177/09544054211014492

Abstract

Collaborative robots are becoming increasingly important for advanced manufacturing processes. The purpose of this paper is to determine the capability of a novel Human-Robot-interface to be used for machine hole drilling. Using a developed voice activation system, environmental factors on speech re...

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Published in: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
ISSN: 0954-4054 2041-2975
Published: SAGE Publications 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa56932
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first_indexed 2021-05-20T09:01:44Z
last_indexed 2021-09-08T03:20:45Z
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spelling 2021-09-07T14:16:57.4018911 v2 56932 2021-05-20 Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction 84c202c256a2950fbc52314df6ec4914 Christian Griffiths Christian Griffiths true false 2021-05-20 GENG Collaborative robots are becoming increasingly important for advanced manufacturing processes. The purpose of this paper is to determine the capability of a novel Human-Robot-interface to be used for machine hole drilling. Using a developed voice activation system, environmental factors on speech recognition accuracy are considered. The research investigates the accuracy of a Mel Frequency Cepstral Coefficients-based feature extraction algorithm which uses Dynamic Time Warping to compare an utterance to a limited, user-dependent dictionary. The developed Speech Recognition method allows for Human-Robot-Interaction using a novel integration method between the voice recognition and robot. The system can be utilised in many manufacturing environments where robot motions can be coupled to voice inputs rather than using time consuming physical interfaces. However, there are limitations to uptake in industries where the volume of background machine noise is high. Journal Article Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 235 12 1939 1948 SAGE Publications 0954-4054 2041-2975 Cobots, dynamic time warping, industrial robots, MEL frequency cepstral coefficients, speech recognition, voice control, human-robot-interaction 1 10 2021 2021-10-01 10.1177/09544054211014492 http://dx.doi.org/10.1177/09544054211014492 COLLEGE NANME General Engineering COLLEGE CODE GENG Swansea University 2021-09-07T14:16:57.4018911 2021-05-20T09:59:34.8574002 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering B Birch 1 Christian Griffiths 2 A Morgan 3 56932__19951__f840a37339684679add495219d5e316e.pdf 56932.pdf 2021-05-20T10:01:19.6232079 Output 1838600 application/pdf Version of Record true true eng http://creativecommons.org/licenses/by/4.0/
title Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
spellingShingle Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
Christian Griffiths
title_short Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
title_full Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
title_fullStr Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
title_full_unstemmed Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
title_sort Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
author_id_str_mv 84c202c256a2950fbc52314df6ec4914
author_id_fullname_str_mv 84c202c256a2950fbc52314df6ec4914_***_Christian Griffiths
author Christian Griffiths
author2 B Birch
Christian Griffiths
A Morgan
format Journal article
container_title Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
container_volume 235
container_issue 12
container_start_page 1939
publishDate 2021
institution Swansea University
issn 0954-4054
2041-2975
doi_str_mv 10.1177/09544054211014492
publisher SAGE Publications
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering
url http://dx.doi.org/10.1177/09544054211014492
document_store_str 1
active_str 0
description Collaborative robots are becoming increasingly important for advanced manufacturing processes. The purpose of this paper is to determine the capability of a novel Human-Robot-interface to be used for machine hole drilling. Using a developed voice activation system, environmental factors on speech recognition accuracy are considered. The research investigates the accuracy of a Mel Frequency Cepstral Coefficients-based feature extraction algorithm which uses Dynamic Time Warping to compare an utterance to a limited, user-dependent dictionary. The developed Speech Recognition method allows for Human-Robot-Interaction using a novel integration method between the voice recognition and robot. The system can be utilised in many manufacturing environments where robot motions can be coupled to voice inputs rather than using time consuming physical interfaces. However, there are limitations to uptake in industries where the volume of background machine noise is high.
published_date 2021-10-01T04:12:16Z
_version_ 1763753838799486976
score 11.012678

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