摘要：
为研究飞机牵引车智能语音控制,实现机场环境下牵引车对飞行员语音命令的精确、高效识别,同时针对传统动态时间规整(DTW)算法计算量大、时间复杂度高、算法识别效率低的问题,提出了一种车辆语音识别的六边形弯曲窗口约束DTW优化算法.首先,从DTW算法原理、牵引车指令的语音特性和机场环境三方面,分析了弯曲窗口对DTW算法识别精度、效率的影响;然后,在Itakura Parallelogram菱形弯曲窗口约束DTW优化算法的基础上,进一步提出了六边形弯曲窗口约束的DTW全局优化算法;最后,通过改变优化系数,实现了最优六边形弯曲窗口约束的DTW算法方案.基于孤立词识别的实验结果表明,所提最优算法与传统DTW算法、菱形弯曲窗口约束的DTW算法相比,识别错误率分别降低77.14％和69.27％,识别效率分别提高48.92％和27.90％.该最优算法更具鲁棒性、时效性,可以作为飞机牵引车智能控制的理想指令输入端口.%In order to study the intelligent voice control of aircraft towing vehicle,realize accurate and efficient recognition of the voice command of pilot in the airport environment,and solve the problems of large computation,high time complexity and low recognition efficiency of the traditional Dynamic Time Warping (DTW) algorithm,a new optimization algorithm of DTW with constraint of hexagonal warping window for vehicle speech recognition was proposed.Firstly,the influence of warping window on the accuracy and efficiency of DTW algorithm was analyzed from three aspects such as the principles of DTW algorithm,the speech characteristics of towing vehicle instruction and the airport environment.Then,on the basis of DTW optmization algorithm with constraint of Itakura Parallelogram rhombic warping window,a DTW global optimization algorithm with the constraint of hexagonal warping window was further proposed.Finally,by varying the optimization coefficient,the optimal DTW algorithm with the constraint of hexagonal warping window was realized.The experimental results based on isolated-word recognition show that,compared with the traditional DTW algorithm and the DTW algorithm with rhombic warping window constraint,the recognition error rate of the proposed optimal algorithm is reduced by 77.14％ and 69.27％ respectively,and its recognition efficiency is increased by 48.92％ and 27.90％ respectively.The proposed optimal algorithm is more robust and timeliness,and can be used as an ideal instruction input port for intelligent control of aircraft towing vehicle.
