An algorithm for optimizing the nonlinear time alignment based on tabu approach
基于禁止搜索的非线性时间匹配优化算法

Dynamic Time Warping(DTW) has been widely used in speech recognition sys-tems as a, nonlinear time alignment technique. It uses the dynamic programniing technique to search the optimal warping path for two time sequences. Although this algorithm needs less computation and shorter training and searching time, it, is a local optimization algorithm. The Tabu Search(TS) algorithm is the generalized heuristic global search tedmique with short-time memory. and suitable for solving many nonlinear optimization problems. This paper applies this teclmique to speech recognition systems, and presents a new algorithm for optimizing time warping based on TS approach, which makes time warping functions optimized globally. Sim-ulation results show that TSTW has better time warping performance than DTW and GTW.