Grants and Contributions:

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Title:

Low-Complexity Speech Recognition for Next Generation Vocal User Interfaces

Agreement Number:

EGP

Agreement Value:

$25,000.00

Agreement Date:

Dec 13, 2017 -

Organization:

Natural Sciences and Engineering Research Council of Canada

Location:

Quebec, CA

Reference Number:

GC-2017-Q3-00438

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:

Gross, Warren (McGill University)

Program:

Engage Grants for universities

Program Purpose:

Artificial intelligence aims to improve the quality of lives of Canadians in many areas such as health care,x000D
information technology, entertainment and industrial automation. Recent advances in machine learning, inx000D
particular deep neural networks, have been shown to provide the best-known solutions to many challengingx000D
problems in image and speech processing. In particular, Fluent.ai, a Montreal-based R&D company, hasx000D
developed a deep learning algorithm for an entirely acoustic voice interface - converting speech data to actionsx000D
directly, eliminating the costly two-step process of first converting speech to text and then converting text tox000D
action. Fluent.ai would like the McGill team to investigate low-complexity implementation of directx000D
speech-to-action machine learning algorithms in constrained-complexity systems. This research project will bex000D
used to assist Fluent.ai in evaluating the applicability of low-complexity neural networks for their customerx000D
needs in products such as smart toys and personal digital assistants.