  This study presents a system for sound source localization in time domain
using a deep residual neural network. Data from the linear 8 channel microphone
array with 3 cm spacing is used by the network for direction estimation. We
propose to use the deep residual network for sound source localization
considering the localization task as a classification task. This study
describes the gathered dataset and developed architecture of the neural
network. We will show the training process and its result in this study. The
developed system was tested on validation part of the dataset and on new data
capture in real time. The accuracy classification of 30 m sec sound frames is
99.2%. The standard deviation of sound source localization is 4{\deg}. The
proposed method of sound source localization was tested inside of speech
recognition pipeline. Its usage decreased word error rate by 1.14% in
comparison with similar speech recognition pipeline using GCC-PHAT sound source
localization.
