ICRA 2011 Paper Abstract


Paper WeP201.1

Hu, Jwu-Sheng (National Chiao Tung University), Lee, Ming-Tang (National Chiao Tung University), Wang, Ting-Chao (National Chiao Tung University)

A Wake-Up-Word Detection Method Using Spatial Eigenspace Consistency and Resonant Curve Similarity

Scheduled for presentation during the Regular Sessions "Cognitive Human-Robot Interaction" (WeP201), Wednesday, May 11, 2011, 15:25−15:40, Room 3B

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on July 14, 2020

Keywords Cognitive Human-Robot Interaction, Recognition, Localization


In this paper, we propose a method to detect the wake-up-word (WUW) using microphone array for human-robot interaction. The consistency of the spatial eigenspaces formed by the speech source at different frequencies and the resonant curve similarity of the WUW are used as the features for detection. These features are processed and detected separately and the result is determined by cascading individual outcome using Bayes risk detector. This proposed method can keep a high recognition rate under very low signal-to-noise ratio (SNR) conditions. In addition, this method can estimate the direction of arrivals of the sound source, and the proposed architecture is easy to expand by adding detectors with other features in the cascaded manner to further improve the recognition rate.



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