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http://dx.doi.org/10.6109/jkiice.2015.19.2.343

Context Recognition Using Environmental Sound for Client Monitoring System  

Ji, Seung-Eun (Department of Computer Science & Engineering, Incheon National University)
Jo, Jun-Yeong (Department of Computer Science & Engineering, Incheon National University)
Lee, Chung-Keun (Department of Computer Science & Engineering, Incheon National University)
Oh, Siwon (Department of Computer Science & Engineering, Incheon National University)
Kim, Wooil (Department of Computer Science & Engineering, Incheon National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.2, 2015 , pp. 343-350 More about this Journal
Abstract
This paper presents a context recognition method using environmental sound signals, which is applied to a mobile-based client monitoring system. Seven acoustic contexts are defined and the corresponding environmental sound signals are obtained for the experiments. To evaluate the performance of the context recognition, MFCC and LPCC method are employed as feature extraction, and statistical pattern recognition method are used employing GMM and HMM as acoustic models, The experimental results show that LPCC and HMM are more effective at improving context recognition accuracy compared to MFCC and GMM respectively. The recognition system using LPCC and HMM obtains 96.03% in recognition accuracy. These results demonstrate that LPCC is effective to represent environmental sounds which contain more various frequency components compared to human speech. They also prove that HMM is more effective to model the time-varying environmental sounds compared to GMM.
Keywords
Environmental sound; Context recognition; LPCC; MFCC; HMM; GMM;
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