STATISTICAL-ACOUSTIC-MODEL ADAPTATION METHOD, ACOUSTIC-MODEL LEARNING METHOD SUITABLE FOR STATISTICAL-ACOUSTIC-MODEL ADAPTATION, STORAGE MEDIUM IN WHICH PARAMETERS FOR BUILDING DEEP NEURAL NETWORK ARE STORED, AND COMPUTER PROGRAM FOR ADAPTING STATISTICAL ACOUSTIC MODEL

摘要

[Object] An object is to provide a statistical acoustic model adaptation method capable of efficient adaptation of an acoustic model using DNN with training data under a specific condition and achieving higher accuracy. [Solution] A method of speaker adaptation of an acoustic model using DNN includes the steps of: storing speech data 90 to 98 of different speakers separately in a first storage device; preparing speaker-by-speaker hidden layer modules 112 to 120; performing preliminary learning of all layers 42, 44, 110, 48, 50, 52 and 54 of a DNN 80 by switching and selecting the speech data 90 to 98 while dynamically replacing a specific layer 110 with hidden layer modules 112 to 120 corresponding to the selected speech data; replacing the specific layer 110 of the DNN that has completed the preliminary learning with an initial hidden layer; and training the DNN with speech data of a specific speaker while fixing parameters of layers other than the initial hidden layer.