Speech Recognition for Endoscopic Automatic Positioning System

Abstract

A novel system for minimally invasive surgery is presented in this paper. The system utilized an Endoscopic Automatic Positioner (EAP) controlled by Speech Recognition Engine to implement the clamping and dynamically positioning of the laparoscope. The motion instructions of the EAP are transformed from voice commands of specific doctor recognized by an improved algorithm named Normalized Average- Dynamic Time Warping (NA-DTW). An embedded platform based on ARM is designed to run the NA-DTW on Windows CE operating system. 1250 groups of experiments from 10 individual speakers demonstrate the performance of DTW. Compared with traditional algorithms, the enhanced algorithm improves the recognition rate from 96.6% to 99.76% and shortens the time of calculation by 51%. The results demonstrate the enhanced algorithm being effective and can satisfy the real time requirement in embedded system.