@inproceedings{8de240d6679a42b0a9f7dead18c02408,
title = "A method to alert user during headset playback by detection of horn in real time",
abstract = "Listening to music with headset while crossing roads often leads to accidents which result mostly in severe injuries to the pedestrians. Many researches have shown that the act of walking on road with headphones is fast becoming a major cause of fatal road accidents [1]. Though the best solution would be avoiding headsets while in traffic, many times people cannot avoid using headsets for various reasons. The accidents can be at least better avoided if the device from which the user is listening can itself detect horn sounds and alert the user of the approaching vehicle. In this paper we describe a way to detect horn sound in real time with {"}Fundamental Frequency Estimation and Sound Energy level Detection{"}. We have developed a solution and tested it with various horn samples collected in the field. The solution functions well to detect the horn and alert the user in real-time.",
keywords = "Autocorrelation, Fundamental Frequency estimation, Horn detection",
author = "Arnob Ghosh and Balaji, {D. Kuldeep} and Periyasamy Paramasivam",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015 ; Conference date: 10-12-2015 Through 12-12-2015",
year = "2016",
month = jun,
day = "9",
doi = "10.1109/RAICS.2015.7488387",
language = "English (US)",
series = "2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "50--54",
booktitle = "2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015",
address = "United States",
}