Papers
1
Total Citations
10
H-Index
1
About
Jianbiao Xiao is a rising star in the field of energy-efficient voice-processing hardware, with key research contributions in keyword spotting (KWS) and speaker verification for edge-AI devices. His most-cited work, a 2024 paper with 10 citations, introduces the KASP processor—a groundbreaking design that achieves 96.8% 10-keyword accuracy while consuming only 1.68μJ per classification. This processor tackles critical real-world challenges by integrating adaptive beamforming to suppress human-voice noise and a progressive wake-up scheme that dramatically reduces power consumption. Xiao’s innovations directly address the limitations of existing KWS systems, which struggle with interference from nearby speakers and high energy demands. By demonstrating a practical, low-power solution for smart home, robotics, and wearable applications, his work bridges the gap between high-accuracy voice recognition and ultra-efficient hardware implementation. This achievement positions him as a key contributor to the next generation of always-on voice interfaces, where energy efficiency and noise robustness are paramount. His research continues to push the boundaries of on-device AI, making voice-controlled systems more reliable and accessible for everyday use.
Research Focus
Key Achievements
Top Papers
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