—In this paper, a Digital Blowing Detection (DBD) algorithm is developed to identify human’s blow sound signal despite variation in sounds signals. Also this project aims to advance the use of the blowing as input mechanism in controlling application. The algorithm was developed by investigating the sound signals characteristics using digital processing techniques and then utilizes the acquired results to detect the blow sound signal. The proposed method used is an elimination method based on the unique energy levels distribution of voice and unvoice signals. A microphone and MATLAB environment were used to develop the algorithm (capture, record and process microphone input signals). The results of the experiments indicate, that the DBD algorithm successfully eliminate non-blow signals and detecting the blow signals with a 75.7%. This paper demonstrated that human blow is a suitable input to devices which operate based on ON-OFF command, also when a rapid response is required, this include a mouse click with no additional hardware is required for the implementation.
—Human computer interaction, non-speech sound detection, non-verbal vocal input, blow detection, assistive technologies.
The authors are with the Department of Computer Engineering, College of Information Technology, University of Bahrain, Kingdom of Bahrain (e-mail: firstname.lastname@example.org).
Cite:Hessa Al-Junaid, Amina Mohamed Saif, and Fatima Yacoop AlWazzan, "Design of Digital Blowing Detector," International Journal of Information and Electronics Engineering vol. 6, no. 3, pp. 180-184, 2016.