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

[Problem] To provide a statistical-acoustic-model adaptation method with which learning data having specific conditions can be used to efficiently adapt acoustic models using deep neural networks (DNN), and with which accuracy can also be improved. [Solution] A speaker adaptation method for acoustic models using DNNs includes: a step in which utterance data (90-98) for different speakers is separately stored in first storage devices; a step in which hidden layer modules (112-120) for separate speakers are prepared; a step in which preliminary learning for all the layers (42, 44, 110, 48, 50, 52, 54) in a DNN (80) is performed while switching and selecting the utterance data (90-98), and dynamically substituting a specific layer (110) with the hidden layer modules (112-120) corresponding to the selected utterance data; a step in which the DNN specific layer (110), after the preliminary learning has been completed therefor, is substituted with an initial hidden layer; and a step in which parameters for layers other than the initial hidden layer are fixed, and speech data of a specific speaker is used to perform DNN learning.