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About
Yihui Fu is a researcher advancing speech and audio processing for human-robot interaction. Her primary research areas include keyword spotting (KWS) and sound source localization (SSL), with a focus on deploying these capabilities on humanoid platforms. She made a notable contribution as a key organizer of the IEEE SLT 2021 Alpha-Mini Speech Challenge, which provided open datasets, defined competition tracks and rules, and established baselines to accelerate deep learning research in KWS and SSL. This challenge has been cited 2 times and has helped spur significant improvements in enabling robots to understand voice commands and locate sound sources in real-world environments. Fu’s work bridges the gap between algorithmic advances and practical robotic systems, making speech interaction more robust and intuitive. Her efforts in creating shared benchmarks and fostering community-driven progress underscore her impact on the field of spoken language technology.
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Top Papers
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