Grants and Contributions:

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Title:

Front-end Signal Processing for Improved Automatic Speech Recognition

Agreement Number:

EGP

Agreement Value:

$25,000.00

Agreement Date:

Mar 7, 2018 -

Organization:

Natural Sciences and Engineering Research Council of Canada

Location:

Quebec, CA

Reference Number:

GC-2017-Q4-01607

Agreement Type:

Grant

Report Type:

Grants and Contributions

Additional Information:

Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019).

Recipient's Legal Name:

Saucier, Antoine (École Polytechnique de Montréal)

Program:

Engage Grants for universities

Program Purpose:

Our partner Fluent.AI develops Automatic Speech Recognition (ASR) systems based on neural networks. Thex000D
performance of ASR systems degrades significantly in the presence of noise. The types of noises that arex000D
relevant occur e.g. on urban sidewalks, construction sites, factory floors or in cars (e.g. radio music orx000D
background conversations). The performance degradation of ASR systems is partly caused by a lack ofx000D
robustness to noise of the data representations used in ASR. To improve the performance of our partner's ASRx000D
systems, we propose to develop a pre-processing method that reduces noises in the speech signal before it isx000D
sent to the ASR engine. Our method is based on independent component analysis.