[Submitted on 22 Sep 2026]
Title:Training Intelligent Voice Assistant Wakeup with Controllable Synthetic Conversations
View a PDF of the paper titled Training Intelligent Voice Assistant Wakeup with Controllable Synthetic Conversations, by Marcin Sowa\'nski and 3 other authors
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Abstract:Wake word detection is a critical component of virtual assistants, serving as the gateway to seamless user interactions. This paper introduces a novel wake-up system that extends traditional direct keyword detection with contextual trigger detection. After an initial wake word activation, the system uses reasoning to distinguish between user commands and unrelated speech, ensuring efficient and context-aware engagement. We present a data generation architecture that produces a 62.3-hour corpus of controllable multi-speaker conversations containing direct invocations, contextual follow-ups, and non-addressed speech. Experimental results demonstrate the effectiveness of the proposed approach across diverse synthetic conversational scenarios. We release the code, dataset and trained models to promote reproducibility and further advancements in intelligent assistant technologies.
Subjects:
Artificial Intelligence (cs.AI)
Cite as: arXiv:2609.27037 [cs.AI]
(or arXiv:2609.27037v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2609.27037
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Marcin Sowanski [view email] [v1] Tue, 22 Sep 2026 20:34:22 UTC (85 KB)
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