Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: In one example, a method includes determining, by a processor (104) of a wearable computing device (102) and based on motion data generated by a motion sensor (106) of the wearable computing device, one or more strokes. In this example, the method also includes generating, by the processor and based on the motion data, a respective attribute vector for each respective stroke from the one or more strokes and classifying, by the processor and based on the respective attribute vector, each respective stroke from the one or more strokes into at least one category. In this example, the method also includes determining, by the processor and based on a gesture library and the at least one category for each stroke from the one or more strokes, a gesture. In this example, the method also includes performing, by the wearable device and based on the gesture, an action.

Abstract: An example method includes displaying, by a display (104) of a wearable device (100), a content card (114B); receiving, by the wearable device, motion data generated by a motion sensor (102) of the wearable device that represents motion of a forearm of a user of the wearable device; responsive to determining, based on the motion data, that the user has performed a movement that includes a supination of the forearm followed by a pronation of the forearm at an acceleration that is less than an acceleration of the supination, displaying, by the display, a next content card (114C); and responsive to determining, based on the motion data, that the user has performed a movement that includes a supination of the forearm followed by a pronation of the forearm at an acceleration that is greater than an acceleration of the supination, displaying, by the display, a previous content card (114A).

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: An example method includes displaying, by a display (104) of a wearable device (100), a content card (114B); receiving, by the wearable device, motion data generated by a motion sensor (102) of the wearable device that represents motion of a forearm of a user of the wearable device; responsive to determining, based on the motion data, that the user has performed a movement that includes a supination of the forearm followed by a pronation of the forearm at an acceleration that is less than an acceleration of the supination, displaying, by the display, a next content card (114C); and responsive to determining, based on the motion data, that the user has performed a movement that includes a supination of the forearm followed by a pronation of the forearm at an acceleration that is greater than an acceleration of the supination, displaying, by the display, a previous content card (114A).

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: An example method includes displaying, by a display (104) of a wearable device (100), a content card (114B); receiving, by the wearable device, motion data generated by a motion sensor (102) of the wearable device that represents motion of a forearm of a user of the wearable device; responsive to determining, based on the motion data, that the user has performed a movement that includes a supination of the forearm followed by a pronation of the forearm at an acceleration that is less than an acceleration of the supination, displaying, by the display, a next content card (114C); and responsive to determining, based on the motion data, that the user has performed a movement that includes a supination of the forearm followed by a pronation of the forearm at an acceleration that is greater than an acceleration of the supination, displaying, by the display, a previous content card (114A).

Abstract: In one example, a method includes determining, by a processor (104) of a wearable computing device (102) and based on motion data generated by a motion sensor (106) of the wearable computing device, one or more strokes. In this example, the method also includes generating, by the processor and based on the motion data, a respective attribute vector for each respective stroke from the one or more strokes and classifying, by the processor and based on the respective attribute vector, each respective stroke from the one or more strokes into at least one category. In this example, the method also includes determining, by the processor and based on a gesture library and the at least one category for each stroke from the one or more strokes, a gesture. In this example, the method also includes performing, by the wearable device and based on the gesture, an action.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing multimodal input. A system configured to practice the method continuously monitors an audio stream associated with a gesture input stream, and detects a speech event in the audio stream. Then the system identifies a temporal window associated with a time of the speech event, and analyzes data from the gesture input stream within the temporal window to identify a gesture event. The system processes the speech event and the gesture event to produce a multimodal command. The gesture in the gesture input stream can be directed to a display, but is remote from the display. The system can analyze the data from the gesture input stream by calculating an average of gesture coordinates within the temporal window.

Abstract: The invention relates to a component comprising a plurality of fiber elements and sample molecules of a selected sample molecule species or of selected sample molecule species groups, said sample molecules being immobilized on said fiber elements, whereby a specific sample molecule species or sample molecule species group is assigned to each fiber element. The invention is characterized in that the sample molecules are immobilized on outer surfaces of the fiber elements, and in that a supporting element fixes the fiber elements in an interspaced manner and in a radial direction with regard to the fiber elements or the fiber elements are bundled together with linear contact.