Title :
A new method for model selection in speech recognition
Author :
Wu, Yahui ; Liu, Gang ; Guo, Jun
Author_Institution :
Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing
Abstract :
A new method based on model selection for acoustic model training is proposed .The MPE trained model and the MLE trained model is used for model selection for the following training. The selection criteria is based on the ratio of the inter-variance to the intra-variance of each model. Besides we also propose a cluster method for the model in order to get the accuracy information for the weight calculation. The experiments demonstrate that the new model can get better performance than any of the directly trained models.
Keywords :
maximum likelihood estimation; speech recognition; accuracy information; acoustic model training; inter-variance; intra-variance; maximum likelihood estimation; minimum phone error; model selection; speech recognition; weight calculation; Computer errors; Hidden Markov models; Intelligent systems; Laboratories; Maximum likelihood estimation; Pattern recognition; Speech analysis; Speech recognition; Statistical analysis; Training data; MLE; MPE; Model selection; speech recognition;
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2008. NLP-KE '08. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4515-8
Electronic_ISBN :
978-1-4244-2780-2
DOI :
10.1109/NLPKE.2008.4906801
