REAL TIME ABNORMAL SOUND DETECTION AND CLASSIFICATION FOR HOME ENVIRONMENT

• Main Author: MOHAMED AMIN, SITI NUR AZIMAH
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi Petronas 2011
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://utpedia.utp.edu.my/8350/1/2011%20-%20Real%20time%20abnormal%20sound%20detection%20and%20classification%20for%20home%20environment.pdf; http://utpedia.utp.edu.my/8350/

This paper is a final report for the final year project titled Real Time Abnormal Sound Detection and Classification for Home Environment. This project utilizes signal processing and signal analyzing techniques to classify any abnormal sounds in any house environment. The project will be applied specifically for surveillance system in the house so that the system could recognise and differentiate the abnormal sounds in house environment. There are various algorithms available to identify and classify the abnormal event sound. In this project, a system is designed to have abnormal sound detection and classification. For abnormal sound detection, mean signal approach being used while for classification process, there two main methods being used which are features extraction using Mel-Frequency Cepstral Coefficient (MFCC) and classifier using Gaussian Mixture Model (GMM). Mel scale frequencies in MFCC are distributed linearly in the low range but logarithmically in the high range. These characteristic corresponds to the physiological of the hnman ear. Therefore, MFCC has assurance of high accuracy in output. Gaussian Mixture Model (GMM) technique is suitable for usage in Matlab software. Signals from sensor will be detected and MFCC will extract the features which meet the requirement decided. The valuable features will be feed in to the classifier GMM. For this project, a microphone will be used as audio sensor, while all programming codes will be tested using Matlab software. As a result, the project would be able to classify the detected any abnormal event sound. The user would be able to employ the system as a supervision and precaution for any unexpected situation.