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Audio Processing For Internet of Things

Rezaei Balef, Amir | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52660 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Gholampour, Iman
  7. Abstract:
  8. Audio signal processing is a greatly useful approach to the Internet of Things since analyzing prominent audio signals can provide valuable information about environmental activities. Environmental sound processing is used in applications such as mechanical systems diagnosis, industrial maintenance, security systems, etc. This approach requires the design and development of sound classification and detection systems. In this thesis, we have achieved 84.5% accuracy on optimizing the features (by feature engineering and feature learning) and exploiting different types of machine learning algorithms. Well-known databases such as ESC-50 have been used to test and evaluate the whole system. Among the machine learning methods, the accuracy of deep learning methods implemented for sound event classification is higher than other rivals for the final system. The accuracy of this method is also higher than human accuracy. Moreover, in this thesis, a sound anomaly detection system is designed and implemented to detect abnormal sound events. These systems are implemented on boards based on low-cost, as well as low-power microcontrollers and single-board computers
  9. Keywords:
  10. Internet of Things ; Machine Learning ; Deep Learning ; Microcontroller ; Audio Processing ; Acoustic Signal Processing ; Sound Events ; Sound Anomaly

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