Abstract
Cue-me™ is one of the reference implementations of the W3C’s multimodal interaction (MMI) architecture and is a context-aware multimodal authoring and run-time platform that securely houses various modality components and facilitates cross-platform development of multimodal applications. It features several multimodal elements such as Face Recognition, Speech Recognition (ASR) and Synthesis (TTS), Digital annotations/gestures (Ink), Motion Sensing and EEG-headset based interactions that were developed using W3C MMI Architecture and Markup Languages. The MMI architecture described elsewhere in this volume facilitates single-authoring of multimodal applications and shields the developers from the nuances of the implementation of individual modality components or their distribution.
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URL’s
Easy Health Assistant use case video: http://youtu.be/x2Tte0QyTiA.
Openstream Easy Health Assistant Mindwave Demo: http://youtu.be/aEgdRU-yM2o.
Poor Medication adherence costs $290 Billion Annually: http://mobilehealthnews.com/3901/poor-medication-costs-290-billion-a-year/.
W3C Multimodal Architecture: http://www.w3.org/TR/mmi-arch/.
Cue-me™ Multimodal Authoring Platform: http://www.openstream.com/cueme.
SCXML – State Chart XML: (http://www.w3.org/TR/scxml/).
Neurosky Mindwave: http://neurosky.com/products-markets/eeg-biosensors/hardware/.
Acknowledgments
Thanks to all the team members of Openstream especially, R. Anthapu, R. Sripada, G. McCobb, K. Patel, N. Shah, T. Sindhaghatta, S. Anthapu, B. Narayana, and S. Khandavilli, who helped in the design and development and the guidance and help provided by D. Dahl, K. Ashimura at W3C MMI.
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Tumuluri, R., Kharidi, N. (2017). Developing Portable Context-Aware Multimodal Applications for Connected Devices Using the W3C Multimodal Architecture. In: Dahl, D. (eds) Multimodal Interaction with W3C Standards. Springer, Cham. https://doi.org/10.1007/978-3-319-42816-1_9
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