Acoustic model learning apparatus, method of the same and program

Abstract

An acoustic model learning apparatus includes a first output probability distribution calculating part that calculates a first output probability distribution including a distribution of output probabilities of respective units of an output layer using a feature amount obtained from an acoustic signal for learning and a learned first acoustic model including a neural network, and the first output probability distribution calculating part obtains the first output probability distribution using a smoothing parameter made up of a real value greater than 0 as input so that the first output probability distribution approaches a uniform distribution as the smoothing parameter is greater, and calculates the first output probability distribution by obtaining logits of respective units of an output layer using the feature amount obtained from the acoustic signal for learning and the first acoustic model and setting a value of the smoothing parameter greater in the case where an output unit number with the greatest logit value is different from a correct unit number than in the case where the output unit number with the greatest logit value matches the correct unit number.