@inproceedings{de9e3c82c7f441dcb9ea1320b3d53f09,
title = "DNN and Clustering Based Binaural Sound Source Localization in Mismatched HRTF Condition",
abstract = "Binaural sound source localization is an important and widely used technique, it has been studied by many researchers based on Head-Related Transfer Functions (HRTF). Due to the individualization of the HRTF technology, the localization performance may be degraded in the mismatched HRTF condition which means the training data and test data are generated by different HRTFs. This paper presents a method based on deep neural network (DNN) and cluster analysis to improve the localization performance in the mismatched HRTF condition. The experimental result shows that the proposed method performs better than the existing methods in the mismatched HRTF condition.",
keywords = "Binuaral, Cluster, DNN, HRTF, Localization",
author = "Jin Wang and Jing Wang and Zhaoyu Yan and Xinyao Wang and Xiang Xie",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 ; Conference date: 11-12-2019 Through 13-12-2019",
year = "2019",
month = dec,
doi = "10.1109/ICSIDP47821.2019.9172979",
language = "English",
series = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
address = "United States",
}