research-article

Ok Google, What Am I Doing?: Acoustic Activity Recognition Bounded by Conversational Assistant Interactions

Authors:

Rebecca Adaimi,

Edison ThomazAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 5, Issue 1

Article No.: 2, Pages 1 - 24

https://doi.org/10.1145/3448090

Published: 30 March 2021 Publication History

Abstract

Conversational assistants in the form of stand-alone devices such as Amazon Echo and Google Home have become popular and embraced by millions of people. By serving as a natural interface to services ranging from home automation to media players, conversational assistants help people perform many tasks with ease, such as setting timers, playing music and managing to-do lists. While these systems offer useful capabilities, they are largely passive and unaware of the human behavioral context in which they are used. In this work, we explore how off-the-shelf conversational assistants can be enhanced with acoustic-based human activity recognition by leveraging the short interval after a voice command is given to the device. Since always-on audio recording can pose privacy concerns, our method is unique in that it does not require capturing and analyzing any audio other than the speech-based interactions between people and their conversational assistants. In particular, we leverage background environmental sounds present in these short duration voice-based interactions to recognize activities of daily living. We conducted a study with 14 participants in 3 different locations in their own homes. We showed that our method can recognize 19 different activities of daily living with average precision of 84.85% and average recall of 85.67% in a leave-one-participant-out performance evaluation with 30-second audio clips bound by the voice interactions.

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Cited By

Takeda NLegaspi RNishimura YIkeda KMinamikawa APlötz TChernova S(2024)Sensor event sequence prediction for proactive smart homeJournal of Ambient Intelligence and Smart Environments10.3233/AIS-23042916:3(275-308)Online publication date: 24-Sep-2024
https://dl.acm.org/doi/10.3233/AIS-230429
Le HLakshminarayanan RLi JMishra VIntille S(2024)Collecting Self-reported Physical Activity and Posture Data Using Audio-based Ecological Momentary AssessmentProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785848:3(1-35)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678584
Trippas JGallagher LMackenzie JSerra ESpezzano F(2024)Re-evaluating the Command-and-Control Paradigm in Conversational Search InteractionsProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679588(2260-2270)Online publication date: 21-Oct-2024
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Index Terms

Ok Google, What Am I Doing?: Acoustic Activity Recognition Bounded by Conversational Assistant Interactions
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 5, Issue 1

March 2021

1272 pages

EISSN:2474-9567

DOI:10.1145/3459088

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Published: 30 March 2021

Published in IMWUT Volume 5, Issue 1

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Cited By

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https://dl.acm.org/doi/10.3233/AIS-230429
Le HLakshminarayanan RLi JMishra VIntille S(2024)Collecting Self-reported Physical Activity and Posture Data Using Audio-based Ecological Momentary AssessmentProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785848:3(1-35)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678584
Trippas JGallagher LMackenzie JSerra ESpezzano F(2024)Re-evaluating the Command-and-Control Paradigm in Conversational Search InteractionsProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679588(2260-2270)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679588
Deng KZhao DZhang ZWang SZheng WMa H(2024)Midas++: Generating Training Data of mmWave Radars From Videos for Privacy-Preserving Human Sensing With MobilityIEEE Transactions on Mobile Computing10.1109/TMC.2023.332539923:6(6650-6666)Online publication date: Jun-2024
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