Reference number : GC-2017-Q3-00438, amendment number : , agreement type : G, recipient legal name : Gross, Warren (McGill University)|Gross, Warren (Université McGill), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : 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, in_x000D_
particular deep neural networks, have been shown to provide the best-known solutions to many challenging_x000D_
problems in image and speech processing. In particular, Fluent.ai, a Montreal-based R&D company, has_x000D_
developed a deep learning algorithm for an entirely acoustic voice interface - converting speech data to actions_x000D_
directly, eliminating the costly two-step process of first converting speech to text and then converting text to_x000D_
action. Fluent.ai would like the McGill team to investigate low-complexity implementation of direct_x000D_
speech-to-action machine learning algorithms in constrained-complexity systems. This research project will be_x000D_
used to assist Fluent.ai in evaluating the applicability of low-complexity neural networks for their customer_x000D_
needs in products such as smart toys and personal digital assistants., program purpose french : 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, in_x000D_
particular deep neural networks, have been shown to provide the best-known solutions to many challenging_x000D_
problems in image and speech processing. In particular, Fluent.ai, a Montreal-based R&D company, has_x000D_
developed a deep learning algorithm for an entirely acoustic voice interface - converting speech data to actions_x000D_
directly, eliminating the costly two-step process of first converting speech to text and then converting text to_x000D_
action. Fluent.ai would like the McGill team to investigate low-complexity implementation of direct_x000D_
speech-to-action machine learning algorithms in constrained-complexity systems. This research project will be_x000D_
used to assist Fluent.ai in evaluating the applicability of low-complexity neural networks for their customer_x000D_
needs in products such as smart toys and personal digital assistants., agreement title english : Low-Complexity Speech Recognition for Next Generation Vocal User Interfaces, agreement title french : Low-Complexity Speech Recognition for Next Generation Vocal User Interfaces, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-12-13, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada