Projects per year
Abstract
We propose a two-stream convolutional network for audio recognition, that operates on time-frequency spectrogram inputs. Following similar success in visual recognition, we learn Slow-Fast auditory streams with separable convolutions and multi-level lateral connections. The Slow pathway has high channel capacity while the Fast pathway operates at a fine-grained temporal resolution. We showcase the importance of our two-stream proposal on two diverse datasets: VGG-Sound and EPIC-KITCHENS-100, and achieve state- of-the-art results on both.
Original language | English |
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Title of host publication | ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Number of pages | 5 |
ISBN (Electronic) | 978-1-7281-7605-5 |
ISBN (Print) | 978-1-7281-7606-2 |
Publication status | E-pub ahead of print - 13 May 2021 |
Publication series
Name | |
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ISSN (Print) | 2379-190X |
Keywords
- training
- visualization
- time-frequency analysis
- convolution
- channel capacity
- conferences
- speech recognition
- audio recognition
- action recognition
- fusion
- multi-stream networks
Fingerprint
Dive into the research topics of 'SLOW-FAST AUDITORY STREAMS FOR AUDIO RECOGNITION'. Together they form a unique fingerprint.Projects
- 1 Active
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UMPIRE: United Model for the Perception of Interactions for visual Recognition
1/02/20 → 31/01/25
Project: Research
Prizes
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Outstanding Paper - ICASSP 2021
Damen, Dima (Recipient) & Kazakos, Vangelis (Recipient), Jun 2021
Prize: Prizes, Medals, Awards and Grants
Equipment
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HPC (High Performance Computing) Facility
Sadaf R Alam (Manager), Steven A Chapman (Manager), Polly E Eccleston (Other), Simon H Atack (Other) & D A G Williams (Manager)
Facility/equipment: Facility