Low-Complexity Speech Recognition for Next Generation Vocal User Interfaces

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