VoCopilot: Voice-Activated Tracking of Everyday Interactions
CoRR(2023)
摘要
Voice plays an important role in our lives by facilitating communication,
conveying emotions, and indicating health. Therefore, tracking vocal
interactions can provide valuable insight into many aspects of our lives. This
paper presents our ongoing efforts to design a new vocal tracking system we
call VoCopilot. VoCopilot is an end-to-end system centered around an
energy-efficient acoustic hardware and firmware combined with advanced machine
learning models. As a result, VoCopilot is able to continuously track
conversations, record them, transcribe them, and then extract useful insights
from them. By utilizing large language models, VoCopilot ensures the user can
extract useful insights from recorded interactions without having to learn
complex machine learning techniques. In order to protect the privacy of end
users, VoCopilot uses a novel wake-up mechanism that only records conversations
of end users. Additionally, all the rest of pipeline can be run on a commodity
computer (Mac Mini M2). In this work, we show the effectiveness of VoCopilot in
real-world environment for two use cases.
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