Abstract: In our living environment, a non-speech audio signal provides a significant evidence for situation awareness. It also compliments the information obtained from a video signal. In non-speech audio signals, screaming is one of the events in which the people like security guard, care taker and family members are particularly interested in terms of care and surveillance because screams are atomically considered as a sign of danger. Contrary to this concept, this review is particularly targeting automated acoustic systems using non-speech class of scream believing that the screams can further be classified into various classes like happiness, sadness, fear, danger, etc. Inspired by the prevalent scream audio detection and classification field, a taxonomy has been projected to highlight the target applications, significant sound features, classification techniques, and their impact on classification problems in last few decades. This review will assist the researchers for retrieving the most appropriate scream detection and classification technique and acoustic parameters for scream classification that can assist in understanding the vocalization condition of the speaker.

Saba Nazir, Muhammad Awais, Sheraz Malik and Fatima Nazir, “A Review on Scream Classification for Situation Understanding” International Journal of Advanced Computer Science and Applications(IJACSA), 9(8), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090809

@article{Nazir2018,
title = {A Review on Scream Classification for Situation Understanding},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090809},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090809},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {8},
author = {Saba Nazir and Muhammad Awais and Sheraz Malik and Fatima Nazir}
}