Sound-based person identification has largely focused on speaker recognition. However, also non-speech sounds may convey personal information, as suggested by our previous studies on hand clap recognition. We propose the use of a probabilistic model-based technique for person identication based on their hand clapping sounds. The method is based on a Hidden Markov Model which uses spectral templates in its observation model. The technique has been evaluated in an experiment with 16 subjects, resulting in an overall correct classication rate of 64 %. The algorithm runs in real-time, making it suitable also for interactive systems.
Jylhä, Antti; Erkut, Cumhur; Simsekli, Umut; Cemgil, A. Taylan
Affiliations: Aalto University School of Electrical Engineering, Aalto, Finland; Bogazici University, Istanbul, Turkey(See document for exact affiliation information.)
AES Conference: 45th International Conference: Applications of Time-Frequency Processing in Audio (March 2012)
Paper Number: 1-4
Publication Date: March 1, 2012
Subject: Processing of Audio
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