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Enabling Hands-Free Voice Assistant Activation on Earphones

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Longfei ShangguanAuthors Info & Claims

MOBISYS '24: Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services

Pages 155 - 168

https://doi.org/10.1145/3643832.3661890

Published: 04 June 2024 Publication History

Abstract

We present the design and implementation of EarVoice, a lightweight mobile service that enables hands-free voice assistant activation on commodity earphones. EarVoice comprises two design modules: one for joint speech detection and primary user identification that explores the attributes of the air channel and in-body audio pathway to differentiate between the primary user and others nearby; and another for accurate wakeup word enhancement, which employs a "copy, paste, and adapt" approach to reconstruct the missing high-frequency component in speech recordings. To minimize false positives, enhance agility, and preserve privacy, we deploy EarVoice on a dongle where the proposed signal processing algorithms are streamlined with a gating mechanism to permit only the primary user's speech to enter the pairing device (e.g., a smartphone) for wakeup word recognition, preventing unintended disclosure of ambient conversations. We implemented the dongle on a 4-layer PCB board and conducted extensive experiments with 23 participants in both controlled and uncontrolled scenarios. The experiment results show that EarVoice achieves around 90% wakeup word recognition accuracy in stationary scenarios, which is on par with the high-end, multi-sensor fusion-based Airpods Pro earbud. EarVoice's performance drops to 84% on mobile cases, slightly worse than Airpods (around 90%).

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Cited By

Parikh VMahmud SAgarwal DLi KGuimbretière FZhang CKostakos VKay JHoang T(2024)EchoGuide: Active Acoustic Guidance for LLM-Based Eating Event Analysis from Egocentric VideosProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676611(40-47)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676611

Index Terms

Enabling Hands-Free Voice Assistant Activation on Earphones
1. Hardware
  1. Emerging technologies
2. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile devices

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cover image ACM Conferences

MOBISYS '24: Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services

June 2024

778 pages

ISBN:9798400705816

DOI:10.1145/3643832

Chairs:
Tadashi Okoshi,
JeongGil Ko,
Program Chair:
Robert LiKamWa

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Published: 04 June 2024

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MOBISYS '24: 22nd Annual International Conference on Mobile Systems, Applications and Services

June 3 - 7, 2024

Minato-ku, Tokyo, Japan

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Cited By

Parikh VMahmud SAgarwal DLi KGuimbretière FZhang CKostakos VKay JHoang T(2024)EchoGuide: Active Acoustic Guidance for LLM-Based Eating Event Analysis from Egocentric VideosProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676611(40-47)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676611

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