Abstract
Speech recognition with visual context is a technique that uses digital image processing to detect lip movements within the frames of a video to predict the words uttered by a speaker. Although models with excellent results already exist, most of them are focused on very controlled environments with few speaker interactions. In this work, a new implementation of a model based on Convolutional Neural Networks (CNN) is proposed, taking into account image frames and three models of audio usage throughout spectrograms. The results obtained are very encouraging in the field of automatic speech recognition.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
