ACOUSTIC MODEL LEARNING APPARATUS, VOICE RECOGNITION EQUIPMENT, ACOUSTIC MODEL LEARNING METHOD, VOICE RECOGNITION METHOD, ACOUSTIC MODEL LEARNING PROGRAM AND VOICE RECOGNITION PROGRAM

摘要

PROBLEM TO BE SOLVED: To enable fast adaptation of parameters for an acoustic model during voice recognition.SOLUTION: In a hidden layer of a neural network as an acoustic model, a weighting matrix Wand a bias vector bare resolved in each of acoustic condition feature values y, which is a k-th element (k is a natural number of 1, 2, ..., k, and represents the number of acoustic conditions) of an acoustic condition feature value vector (yincluded in R) (K-dimentional actual number space) extracted from an n-th frame in the acoustic condition feature value vectors which represents an acoustic condition feature value. When recognizing voice, a linear transformation is performed for each the resolved hidden layers based on the acoustic condition feature value y, and is automatically adapted to the acoustic condition.SELECTED DRAWING: Figure 1