Patent application number | Description | Published |
20130090926 | MOBILE DEVICE CONTEXT INFORMATION USING SPEECH DETECTION - Systems and methods for speech detection in association with a mobile device are described herein. A method described herein for identifying presence of speech associated with a mobile device includes obtaining a plurality of audio samples from the mobile device while the mobile device operates in a mode distinct from a voice call operating mode, generating spectrogram data from the plurality of audio samples, and determining whether the plurality of audio samples include information indicative of speech by classifying the spectrogram data. | 04-11-2013 |
20130297547 | AGGREGATE CONTEXT INFERENCES USING MULTIPLE CONTEXT STREAMS - Methods, systems, computer-readable media, and apparatuses for inferring context are provided. In one potential implementation, first context information associated with a first duration is identified, second context information is accessed to determine a context segmentation boundary; and the first context information and the second context information is then aggregated to generate an inferred segmented aggregated context. In a further implementation, the first context information is used to average inferred contexts, and the context segmentation boundary is used to reset a start time for averaging the first context information. | 11-07-2013 |
20130303198 | INFERRING A CONTEXT FROM CROWD-SOURCED ACTIVITY DATA - Techniques are provided to infer a context associated with a mobile device based on aggregated data from a set of other mobile devices. The set of mobile devices can include mobile devices currently or previously near a location of the mobile device. Each mobile device in the set of other mobile devices can collect sensor data and infer a low-level context (e.g., “sitting” or “standing”). The low-level contexts can be aggregated. Based on the aggregated low-level contexts, a high-level context (e.g., “at a party” or “watching television”) associated with the mobile device can be inferred or a low-level context associated with the mobile device can be refined. | 11-14-2013 |
20130317821 | SPARSE SIGNAL DETECTION WITH MISMATCHED MODELS - Various arrangements for detecting a type of sound, such as speech, are presented. A plurality of audio snippets may be sampled. A period of time may elapse between consecutive audio snippets. A hypothetical test may be performed using the sampled plurality of audio snippets. Such a hypothetical test may include weighting one or more hypothetical values greater than one or more other hypothetical values. Each hypothetical value may correspond to an audio snippet of the plurality of audio snippets. The hypothetical test may further include using at least the greater weighted one or more hypothetical values to determine whether at least one audio snippet of the plurality of audio snippets comprises the type of sound. | 11-28-2013 |
20140129560 | CONTEXT LABELS FOR DATA CLUSTERS - Systems and methods for applying and using context labels for data clusters are provided herein. A method described herein for managing a context model associated with a mobile device includes obtaining first data points associated with a first data stream assigned to one or more first data sources; assigning ones of the first data points to respective clusters of a set of clusters such that each cluster is respectively assigned ones of the first data points that exhibit a threshold amount of similarity and are associated with times within a threshold amount of time of each other; compiling statistical features and inferences corresponding to the first data stream or one or more other data streams assigned to respective other data sources; assigning context labels to each of the set of clusters based on the statistical features and inferences. | 05-08-2014 |
20140143579 | SEQUENTIAL FEATURE COMPUTATION FOR POWER EFFICIENT CLASSIFICATION - Disclosed is an apparatus and method for power efficient processor scheduling of features. In one embodiment, features may be scheduled for sequential computing, and each scheduled feature may receive a sensor data sample as input. In one embodiment, scheduling may be based at least in part on each respective feature's estimated power usage. In one embodiment, a first feature in the sequential schedule of features may be computed and before computing a second feature in the sequential schedule of features, a termination condition may be evaluated. | 05-22-2014 |
20140156659 | FUSING CONTEXTUAL INFERENCES SEMANTICALLY - System and methods for performing context inference in a computing device are disclosed. In one embodiment, a method of performing context inference includes: determining, at a computing device, a first context class using context-related data from at least one data source associated with a mobile device; and determining, at the mobile device, a fusion class based on the first context class, the fusion class being associated with at least one characteristic that is common to the first context class and a second context class that is different from the first context class. | 06-05-2014 |
20140179298 | LOW POWER ALWAYS-ON DETERMINATION OF INDOOR VERSUS OUTDOOR STATE - Methods, systems, computer-readable media, and apparatuses for determining indoor/outdoor state of a mobile device are presented. In some embodiments, a mobile device may maintain an indoor/outdoor state. The mobile device may include at least one first sensor and at least one second sensor, the first sensor associated with higher power consumption than the second sensor. The mobile device may gate off the first sensor and using the second sensor to obtain a sensor reading, if the second sensor can generate a reading indicative of the indoor/outdoor state of the mobile device. The mobile device may use the first sensor to obtain a sensor reading, if the second sensor cannot generate a reading indicative of the indoor/outdoor state of the mobile device. The mobile device may update the indoor/outdoor state of the mobile device based on a reading received from one of the first and the second sensors. | 06-26-2014 |
20140247206 | ADAPTIVE SENSOR SAMPLING FOR POWER EFFICIENT CONTEXT AWARE INFERENCES - Disclosed is a system, apparatus, computer readable storage medium, and method to perform a context inference for a mobile device. In one embodiment, a data processing system includes a processor and a storage device configurable to store instructions to perform a context inference for the data processing system. Data may be received from at least a first sensor, and a first classification of the data from the sensor may be performed. Confidence for the first classification can be determined and a second sensor can be activated based on a determination that the confidence fails to meet a confidence threshold. A data sample classification from the activated second sensor may be classified jointly with the data from first sensor | 09-04-2014 |
20140267799 | ALWAYS-ON CAMERA SAMPLING STRATEGIES - Embodiments of the present invention are directed toward providing intelligent sampling strategies that make efficient use of an always-on camera. To do so, embodiments can utilize sensor information to determine contextual information regarding the mobile device and/or a user of the mobile device. A sampling rate of the always-on camera can then be modulated based on the contextual information. | 09-18-2014 |
20140269363 | IN-TRANSIT DETECTION USING LOW COMPLEXITY ALGORITHM FUSION AND PHONE STATE HEURISTICS - System and methods are disclosed to use information available on the state of mobile devices in a heuristics-based approach to improve motion state detection. In one or more embodiments, information on the WiFi connectivity of mobile devices may be used to improve the detection of the in-transit state. The WiFi connectivity information may be used with sensor signal such as accelerometer signals in a motion classifier to reduce the false positives of the in-transit state. In one or more embodiments, information that a mobile device is connected to a WiFi access point (AP) may be used as heuristics to reduce the probability of falsely classifying the mobile device in the in-transit state when mobile device is actually in the hand of a relatively stationary user. Information on the battery charging state or the wireless connectivity of the mobile devices may also be used to improve the detection of in-transit state. | 09-18-2014 |
20140269555 | SYSTEMS AND METHODS FOR SHARING CONTEXT INFORMATION IN A NEIGHBOR AWARE NETWORK - Systems and methods share context information on a neighbor aware network. A method for communicating data in a wireless communications network is disclosed. The method includes receiving, by a device, a first message from a station, decoding the message to determine service information, the service information identifying a service provided by the station, generating a second message, wherein the second message is generated to indicate the service provided by the station and service information of the device, and transmitting, by the device, the second message to a remote station. | 09-18-2014 |
20140269658 | SYSTEMS AND METHODS FOR SHARING CONTEXT INFORMATION IN A NEIGHBOR AWARE NETWORK - Systems and methods share context information on a neighbor aware network. In one aspect, a context providing device receives a plurality of responses to a discovery query from a context consuming device, and tailors services it offers to the context consuming device based on the responses. In another aspect, a context providing device indicates in its response to a discovery query which services or local context information it can provide to the context consuming device, and also a cost associated with providing the service or the local context information. In some aspects, the cost is in units of monetary currency. In other aspects, the cost is in units of user interface display made available to an entity associated with the context providing device in exchange for the services or local context information offered to the context consuming device. | 09-18-2014 |
20140279790 | CONTEXT AWARE LOCALIZATION, MAPPING, AND TRACKING - Exemplary methods, apparatuses, and systems infer a context of a user or device. A computer vision parameter is configured according to the inferred context. Performing a computer vision task, in accordance with the configured computer vision parameter. The computer vision task may by at least one of: a visual mapping of an environment of the device, a visual localization of the device or an object within the environment of the device, or a visual tracking of the device within the environment of the device. | 09-18-2014 |
20140361905 | CONTEXT MONITORING - Disclosed is a system, apparatus, computer readable storage medium, and method to perform a transition triggered context monitoring for a mobile device. A first sensor data stream comprising data from one or more sensors at the mobile device is received. One or more features calculated from the data of the first sensor data stream may be monitored and a status change for the one or more features is detected. In response to detecting the status change, of a second sensor data stream comprising data from one or more sensors at the mobile device is collected. The second sensor data stream may be processed as a context label for a segment of the first sensor data stream and the segment beginning may be defined by the status change. | 12-11-2014 |
20150066422 | HALF STEP FREQUENCY FEATURE FOR RELIABLE MOTION CLASSIFICATION - Disclosed is an apparatus and method for classifying a motion state of a mobile device. In one embodiment, accelerometer data representing acceleration components along orthogonal x, y, and z axes of the mobile device are collected. A presence or absence of a half-step frequency relationship between the accelerometer data is determined. Last, the motion state of the device is determined based at least in part on the presence or absence of the half-step frequency relationship. | 03-05-2015 |
20150071102 | MOTION CLASSIFICATION USING A COMBINATION OF LOW-POWER SENSOR DATA AND MODEM INFORMATION - Disclosed is an apparatus and method for motion classification using a combination of low-power sensor data and modem information. In one embodiment, data received from at least one low-power sensor is collected. Information regarding cellular network signals is collected from a modem. A speed estimate is determined based on the information regarding cellular network signals. A motion context classification is then determined based on a combination of the collected data received from the at least one low-power sensor and the speed estimate. | 03-12-2015 |