Method of speech recognition using SVM optimized by mutated fish swarm algorithm

The invention relates to the technical field of speech recognition, provides a method of speech recognition using an SVM optimized by a mutated fish swarm algorithm. The visual field of mutated fish is improved adaptively. In the initial stage of iteration of the mutated fish swarm algorithm, the gen value is smaller, the visual field is larger, and individual fish can be updated within the entire traversal range. In the later stage of iteration, as the gen value increases, the visual field gradually narrows, and individual fish is optimized and updated within a small range, which is more conductive to finding a global optimal value accurately. By reducing the use of parameters and simplifying the behavior mode in the artificial fish swarm algorithm, the structure and the computational complexity of the mutated fish swarm algorithm are reduced, the problem that the algorithm gets trapped into local optimum in the process of parameter optimization is avoided effectively, and convergence is accelerated. When th