Statistical acoustic model adaptation method, acoustic model learning method suitable for statistical acoustic model adaptation, storage medium storing parameters for building deep neural network, 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.