Amazon Technologies, Inc.

Upcall Inc.

Michael Devyver

Omar Sze Leung

Leo Benedict Baldwin

Serkan Hatipoglu

Amit Singh Chhetri

Noam Sorek

David William Devries

Stewart Robin Shearer

Aleksandar Pance

Ming Zheng

Mashhour Solh

Jerry Weiming Kuo

Mudit Sunilkumar Khasgiwala

Jason Rute

Willy Horng Jean Cheung

A system may obtain audio files of phone calls and predict the outcomes of the phone calls using a machine learning model. The system may translate the audio files to text transcripts and convert the text transcripts into vectors. The vectors may be input into a machine learning model trained on prior examples of phone calls and their true outcomes. The machine learning model may output a predicted classification of the outcome of the phone call.

Automatic call classification using machine learning

A decision engine executing on an electronic device may determine, using sensor data captured by multiple sensors of the device, whether a user is present in an environment that includes the device. If the user is determined to be present in the environment, the device may transition from a first state to a second state. The first state may be a first power state of the device in which the device is powered off or an idle or dormant state in which the device is powered on but a display of the device is powered off. Correspondingly, the second state may be a second power state of the device in which the device and the display are powered on and content is being rendered on the display. If the decision engine cannot make a determination based on the sensor data, a context engine may adjudicate the user presence determination.

Determining a device state based on user presence detection

Systems and methods for addressing an inadvertent decrease in transmission energy/power due to triggering a proximity sensor by a cover disposed on a computing device. In an embodiment, a cover sensor may be incorporated into the device. The cover sensor may be used to detect the presence of a cover on the device, as well as whether the cover is in an open or closed position. The output of the cover sensor may then be used to adjust a trigger/proximity threshold of the proximity sensor to account for the presence and position of the cover on the device. In this manner the device may avoid unnecessary power backoff caused by proximity of the cover, rather than proximity of the user. This improves the over the air (OTA) performance of the device, as well as the user experience.

Proximity sensor arrangement for wireless devices

Provided are systems and methods for smoke and fire detection. An example method includes receiving two or more image frames that represent images of two or more areas, combining the two or more image frames to generate a composite image frame that represents an image of an area comprising the two or more areas, comparing the composite image frame to a background frame associated with the area to determine one or more pixels of the composite frame having a pixel value that is different from corresponding pixels of the background frame, determining a smoke frame, wherein pixels of the smoke frame that correspond to the one or more pixels of the composite frame comprise a pixel value associated with smoke, determining a smoke value corresponding to pixel values of the pixels of the smoke frame, determining that the smoke value exceeds a smoke threshold value, determining a smoke or fire condition based at least in part on determining that the smoke value exceeds a smoke threshold value, and providing an indication of the smoke or fire condition.

Systems and methods for smoke detection

Described are techniques and systems for determining presence of airborne particles using one or more sensors on a user device. The airborne particles include, but are not limited to, smoke resulting from combustion, dust, fog, and so forth. In one implementation, an optical proximity sensor may be used to determine a distance to an object such as a ceiling. Smoke which collects on the ceiling reflects light that is detected by the proximity sensor and results in an apparent reduction in height. A notification of this change in height may be generated. In other implementations, other techniques may be used to detect airborne particles, such as images from a camera, dedicated particular sensors, and so forth. Information about airborne particles may aid user safety. For example, an alarm may be issued indicating a potential fire or unsafe level of pollution.

Airborne particle detection with user device

Systems and methods are provided for determining a light intensity level of emitted light from an illuminator of a display device and the ambient light surrounding the display device such that, for example, the display device may compensate for performance variations of the illuminator over time.

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Palo Alto, CA, United States of America

Michael Devyver