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2021 | OriginalPaper | Chapter

Comparison of Speech Recognition and Natural Language Understanding Frameworks for Detection of Dangers with Smart Wearables

Authors : Dariusz Mrozek, Szymon Kwaśnicki, Vaidy Sunderam, Bożena Małysiak-Mrozek, Krzysztof Tokarz, Stanisław Kozielski

Published in: Computational Science – ICCS 2021

Publisher: Springer International Publishing

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Abstract

Wearable IoT devices that can register and transmit human voice can be invaluable in personal situations, such as summoning assistance in emergency healthcare situations. Such applications would benefit greatly from automated voice analysis to detect and classify voice signals. In this paper, we compare selected Speech Recognition (SR) and Natural Language Understanding (NLU) frameworks for Cloud-based detection of voice-based assistance calls. We experimentally test several services for speech-to-text transcription and intention recognition available on selected large Cloud platforms. Finally, we evaluate the influence of the manner of speaking and ambient noise on the quality of recognition of emergency calls. Our results show that many services can correctly translate voice to text and provide a correct interpretation of caller intent. Still, speech artifacts (tone, accent, diction), which can differ even for each individual in various situations, significantly influences the performance of speech recognition.

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Title: Comparison of Speech Recognition and Natural Language Understanding Frameworks for Detection of Dangers with Smart Wearables
Authors: Dariusz Mrozek
Szymon Kwaśnicki
Vaidy Sunderam
Bożena Małysiak-Mrozek
Krzysztof Tokarz
Stanisław Kozielski
Publisher: Springer International Publishing
Book: Computational Science – ICCS 2021
Print ISBN: 978-3-030-77969-6

Electronic ISBN: 978-3-030-77970-2

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-77970-2_36

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