Input Intelligence on Mobile Devices

Over the past decade, the confluence of sophisticated algorithms and tools, computational infrastructure, and data science has fueled a machine learning revolution across multiple fields, including speech and handwriting recognition, natural language processing, computer vision, social network filtering, and machine translation. Ensuing advances are changing the way we interact with technology in our daily lives. This is particularly salient when it comes to user input on mobile devices, be it speech, handwriting, touch, keyboard, or camera input. Increased input intelligence boosts device responsiveness across languages, improving not only basic abilities like tokenization, named entity recognition and part-of-speech tagging, but also more advanced capabilities like statistical language modeling and question answering. In this talk, I will give selected examples of what we are doing at Apple to impart input intelligence to mobile devices, with two overarching themes as sub-text: (i) enhancing interaction experience through machine learning, and (ii) transforming users’ digital lives without sacrificing their privacy.

Co-sponsored by: North Jersey Section

Speaker(s): Dr. Jerome R. Bellegarda ,

Agenda:
Over the past decade, the confluence of sophisticated algorithms and tools, computational infrastructure, and data science has fueled a machine learning revolution across multiple fields, including speech and handwriting recognition, natural language processing, computer vision, social network filtering, and machine translation. Ensuing advances are changing the way we interact with technology in our daily lives. This is particularly salient when it comes to user input on mobile devices, be it speech, handwriting, touch, keyboard, or camera input. Increased input intelligence boosts device responsiveness across languages, improving not only basic abilities like tokenization, named entity recognition and part-of-speech tagging, but also more advanced capabilities like statistical language modeling and question answering. In this talk, I will give selected examples of what we are doing at Apple to impart input intelligence to mobile devices, with two overarching themes as sub-text: (i) enhancing interaction experience through machine learning, and (ii) transforming users’ digital lives without sacrificing their privacy.

Room: M105, Bldg: Muscarelle Center, M105, , 1000 River Road , Teaneck , New Jersey, United States, 07666, Virtual: https://events.vtools.ieee.org/m/306840