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METHOD FOR PRESENTING GAUSSIAN PROBABILITY DENSITY AND METHOD OF SPEECH RECOGNITION TRAINING FOR OBTAINING THE SAME
METHOD FOR PRESENTING GAUSSIAN PROBABILITY DENSITY AND METHOD OF SPEECH RECOGNITION TRAINING FOR OBTAINING THE SAME
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机译:高斯概率密度的表示方法和语音识别训练的方法
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摘要
PURPOSE: A method for expressing Gaussian probability density and a voice recognition training method are provided to easily obtain HPGAM(Hybrid Partitioned Gaussian Autoregressive mixture) having a better recognition ratio than a prior GAM(Gaussian Autoregressive mixture) and PGAM(Partitioned Gaussian Autoregressive mixture). CONSTITUTION: A probabiity density space is divided (401) into many PGAM spaces. The divided PGAM space is expressed (402) as a GAM. The highest GAM is expressed (403) as HPGAM, thereby expressing a Gaussian probability density. A voice recognition model in which the nuimber of mixture groups are initialized, a trained voice recognition model is obtained by a recognition training. A voice recognition test is made to the trained voice recognition model, a recognition tranining is made about a mis-recognition word. A new voice recognition model is obtained. A new voice recognition model having the increased number of mixture groups is obtained. A recognition training is performed to the obtained voice recognition model, and it is checked that the number of groups reaches to a desired number. If the number of groups reaches to the desired number, a voice recognition training is terminated.
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