INTEGRATED TRAINING METHOD AND APPARATUS FOR DETECTING VOICES BASED ON DENOISING VARIATIONAL AUTOENCODER

摘要

Provided are an integrated training method and an apparatus for detecting voices based on a denoising variational autoencoder. The integrated training method for detecting voices based on a denoising variational autoencoder comprises the steps of: using batch normalization in order to reduce a phenomenon of an internal covariate shift occurring in training; using a gradient weighting method so that a voice quality-improving deep neural network (DNN) can output voice characteristics needed to detect voices; and using a denoising variational autoencoder in the voice quality-improving DNN, wherein the integrated training method for detecting voices modifies voice characteristics so that noises can be removed from the voice characteristics through the voice quality-improving DNN, and performs voice detection through a voice-detecting DNN by using the voice characteristics whose noises are removed. The present invention can reduce shift of internal covariate by adding a batch normalization layer between two networks.;COPYRIGHT KIPO 2020