An Optimized Method of VQ Codebook Based on Genetic Algorithm
Wang Sheguo
Abstract
Wang Sheguo
Abstract
Vector Quantization(VQ) is one of popular data compression and data coding methods for speech recognition at present.In the process of codebook design,traditional LBG algorithm owns the advantage of fast convergence,but it is easy to get the local optimal result and be influenced by initial codebook.Genetic Algorithm(GA) has the capability of getting global optimal result,a new clustering algorithm GAL which is based on GA and LBG to improve the quality of codebook.The(GA)L algorithm is applied to continuous speech recognition,the experiments show it is more effective than traditional LBG algorithm.
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Vector Quantization(VQ) is one of popular data compression and data coding methods for speech recognition at present.In the process of codebook design,traditional LBG algorithm owns the advantage of fast convergence,but it is easy to get the local optimal result and be influenced by initial codebook.Genetic Algorithm(GA) has the capability of getting global optimal result,a new clustering algorithm GAL which is based on GA and LBG to improve the quality of codebook.The(GA)L algorithm is applied to continuous speech recognition,the experiments show it is more effective than traditional LBG algorithm.
Key concepts: Codebook, Linde–Buzo–Gray algorithm, Vector quantization, Cluster analysis, Algorithm, Computer science, Genetic algorithm, Coding (social sciences)