Projects per year
Abstract
In this work, we propose a sound event detection system based on a parallel capsule neural network. The system takes advantage of the capability of capsule neural networks in the detection of overlapping objects. It further develops a parallel architecture and uses the kernel design of different shapes and sizes to effectively utilize the feature information to increase the detection accuracy. The experimental results show that the performance of the proposed system is as low as 52.34% measured by the error rate, which is even lower than the rank 1 system in DCASE2017 challenge.
Original language | English |
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Title of host publication | 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1933-1936 |
Number of pages | 4 |
ISBN (Electronic) | 9781728132488 |
DOIs | |
State | Published - Nov 2019 |
Event | 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 - Lanzhou, China Duration: 18 Nov 2019 → 21 Nov 2019 |
Publication series
Name | 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 |
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Conference
Conference | 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 |
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Country/Territory | China |
City | Lanzhou |
Period | 18/11/19 → 21/11/19 |
Keywords
- Capsule Neural Network
- Computational Auditory Scene Analysis
- Deep Learning
- Sound Event Detection
Fingerprint
Dive into the research topics of 'Parallel capsule neural networks for sound event detection'. Together they form a unique fingerprint.Projects
- 2 Finished
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Deep Intelligence Based Spoken Language Processing( II )
Wang, J.-C. (PI)
1/01/19 → 31/12/19
Project: Research
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自駕車之深度學習智能感知與情境理解系統技術-自駕車之深度學習智 能感知與情境理解系統技術-子計畫四
Chang, P.-C. (PI)
1/12/18 → 31/07/19
Project: Research