Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150525
Title: Sound recognition from machine learning
Authors: Xiong, Ziqin
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Xiong, Z. (2021). Sound recognition from machine learning. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150525
Abstract: Audio event detection has always been a hot research field of acoustics com- bined with computer science. The research of audio event detection has impor- tant academic significance and commercial value. With the development of ma- chine learning and artificial intelligence, more and more machine learning and deep learning methods have been used in audio event detection, and achieved good results. In recent years, the success of self attention mechanism in the field of computer vision and natural language processing proves that self atten- tion mechanism has great potential. In this dissertation, self attention mechanism (CBAM) is transferred to the field of audio event detection, and theoretical ex- ploration and experimental proof are carried out.
URI: https://hdl.handle.net/10356/150525
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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