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Not All Fallbacks Are Failures: Understanding and Recovering from Fallbacks in Mobile Voice Assistants

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Robust understanding of user input is a core requirement for voice assistants deployed in real-world environments. In practice, these systems encounter heterogeneous fallback situations caused by noisy audio input, transcription errors, ambiguous requests, incomplete utterances, or unintended activations. Existing systems typically respond with generic fallback messages, which do not resolve the underlying interaction failure and can degrade user experience. We study fallback handling in a deployed smartwatch-based voice assistant for general health support in everyday environments. Our analys

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