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Grant Award View - GA28407

Integrating biologically-inspired auditory models into deep learning

Contact Details

ARC NCGP General Enquiries

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02 6287 6600

:

GA ID:
GA28407
Agency:
Australian Research Council
Approval Date:
27-Nov-2018
Publish Date:
18-Dec-2018
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Apr-2019 to 31-Dec-2022
Original: 1-Jan-2019 to 31-Dec-2021
Value (AUD):
$385,000.00 (GST inclusive where applicable)
Variations:

One-off/Ad hoc:
No
Aggregate Grant Award:
No

PBS Program Name:
ARC 18/19 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Integrating biologically-inspired auditory models into deep learning
Purpose:
This project aims to discover how a biologically inspired auditory model can be tightly integrated into a state-of-the-art deep learning speech processing framework, to model, design and verify a deep learning based auditory model. Voice-based technologies, ranging from cochlear implants to smart homes, are growing at a rapid pace and speech interfaces are being integrated with all aspects of our lives. However, there is a growing demand to improve these voice-enabled services, making them more secure and less open to cyber-crime attack by unauthorised users. The project is expected to improve techniques for modelling and automatic processing of speech and audio signals, which should provide significant benefits, including improved voice biometrics and cochlear implants.

GO ID:
GO Title:
Discovery Projects commencing in 2019
Internal Reference ID:
DP19 Round 1
Selection Process:
Targeted or Restricted Competitive

Confidentiality - Contract:
No
Confidentiality - Outputs:
No

Grant Recipient Details

Recipient Name:
The University of New South Wales
Recipient ABN:
57 195 873 179

Grant Recipient Location

Suburb:
KENSINGTON
Town/City:
KENSINGTON
Postcode:
2033
State/Territory:
NSW
Country:
AUSTRALIA

Grant Delivery Location

State/Territory:
NSW
Postcode:
2033
Country:
AUSTRALIA

Contact Details

ARC NCGP General Enquiries

:
02 6287 6600

: