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Multimodal Interface for Ambient Assisted Living

Multimodal interfaces seamlessly integrate two or more user inputs in a coordinated manner to enhance user interaction with the system. This work proposes a multimodal interface that makes use of hand tracking and speech interactions for Ambient Intelligent and Ambient Assisted Living environments. The system is composed of two main modules: Spoken Language Interaction module and Hand Tracking Interaction module. Spoken Language Interaction use speech recognition services to input the user utterance to a natural language understanding module from which the dialog manager will match the context and output the corresponding answer to the user. Hand Tracking Interactions is performed using a Microsoft Kinect device to detect the 3D coordinate of the hand which is stabilized and transformed to be used as a cursor on the screen. Tests have been run on the speech recognition and natural language understanding framework and reached an accuracy of 83.7% in offering the user a correct answer from the first try. The accuracy results of the Dialog manager in offering the user a correct output was 91.6% computed on a data set of 3900 sentences.