Deng Xingjuan, Chen Ji, Shuai Jie
College of Bioengineering, Chongqing Uniwversity, Chongqing 400030, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2009 Aug;26(4):886-9, 899.
For the purpose of improving the efficiency of aphasia rehabilitation training, artificial intelligence-scheduling function is added in the aphasia rehabilitation software, and the software's performance is improved. With the characteristics of aphasia patient's voice as well as with the need of artificial intelligence-scheduling functions under consideration, the present authors have designed a set of endpoint detection algorithm. It determines the reference endpoints, then extracts every word and ensures the reasonable segmentation points between consonants and vowels, using the reference endpoints. The results of experiments show that the algorithm is able to attain the objects of detection at a higher accuracy rate. Therefore, it is applicable to the detection of endpoint on aphasia-patient's voice.
为提高失语症康复训练效率,在失语症康复软件中增加了人工智能调度功能,提升了软件性能。考虑到失语症患者语音的特点以及人工智能调度功能的需求,作者设计了一套端点检测算法。该算法确定参考端点,然后利用参考端点提取每个单词并确保辅音和元音之间的合理分割点。实验结果表明,该算法能够以较高的准确率达到检测目的。因此,它适用于失语症患者语音端点的检测。