Sound recognition from machine learning
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 le...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis-Master by Coursework |
| Language: | English |
| Published: |
Nanyang Technological University
2021
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/150525 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
|---|