Wake-Up-Word Detection for Robots Using Spatial Eigenspace Consistency and Resonant Curve Similarity
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.
Jwu-Sheng Hu Ming-Tang Lee Ting-Chao Wang
National Chiao Tung University,Hshinchu,Taiwan,ROC
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
3901-3906
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）