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Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction
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...
Published in: | Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture |
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ISSN: | 0954-4054 2041-2975 |
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SAGE Publications
2021
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URI: | https://cronfa.swan.ac.uk/Record/cronfa56932 |
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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 |
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1763753838799486976 |
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11.0241995 |