Abstract: Implementations disclosed herein relate to mitigating the reality gap through training a simulation-to-real machine learning model (“Sim2Real” model) using a vision-based robot task machine learning model. The vision-based robot task machine learning model can be, for example, a reinforcement learning (“RL”) neural network model (RL-network), such as an RL-network that represents a Q-function.

Abstract: Devices and methods for electrostatic application of cosmetics are described. In one embodiment, a system for electrostatic deposition of cosmetic material on a surface includes: a housing; a nozzle configured for breaking the cosmetic material into cosmetic particles and for directing the cosmetic particles out of the housing and toward the surface; and a reservoir configured for holding the cosmetic material. The reservoir is connected to the nozzle. The system also includes an airflow conduit configured to provide air to the nozzle; and a nozzle electrode configured proximately to the nozzle. The nozzle electrode is configured to charge the cosmetic particles.

Abstract: A computing device comprising a processor, the processor configured to: receive, from an image capture system, an image captured in an environment and image metadata associated with the image, the image metadata comprising an image capture time; receive a sound recognition message from a sound recognition module, the sound recognition message comprising (i) a sound recognition identifier indicating a target sound or scene that has been recognised based on captured audio data captured in the environment, and (ii) time information associated with the sound recognition identifier; detect that the target sound or scene occurred at a time that the image was captured based on the image metadata and the time information in the sound recognition message; and output a camera control command to said image capture system based on said detection.

Abstract: Verification of presence of a detected target is carried out following an initial presence determination on the basis of detected non-verbal sound.

Abstract: Control of navigation of a content item is carried out by detection of non-verbal sound events. On the basis of receipt of one or more non-verbal sound event reports, a navigation tool is provided with a corresponding sequence of navigation commands. The correspondence between navigation command sequences and non-verbal sound events is established through analysis or markup of the content item.

Abstract: A method for generating a health indicator for at least one person of a group of people, the method comprising: receiving, at a processor, captured sound, where the captured sound is sound captured from the group of people; comparing the captured sound to a plurality of sound models to detect at least one non-speech sound event in the captured sound, each of the plurality of sound models associated with a respective health-related sound type; determining metadata associated with the at least one non-speech sound event; assigning the at least one non-speech sound event and the metadata to at least one person of the group of people; and outputting a message identifying the at least one non-speech event and the metadata to a health indicator generator module to generate a health indicator for the at least one person to whom the at least one non-speech sound event is assigned.

Abstract: A device or system is provided which is configured to detect one or more sound events and/or scenes associated with a predetermined context, and to provide an assistive output on fulfilment of that context.

Abstract: A computing device, the computing device comprising: a location data processing module configured to receive location data from a location sensor of the computing device and output location information; a sound data processing module configured to receive audio data from a microphone of the computing device and output audio information relating to one or more non-verbal sounds of an environment of the computing device captured by the microphone; and an augmentation module configured to: receive the location information and the audio information; generate augmented location data, the augmented location data comprising the location information and the audio information; and output the augmented location data for storage in a data store.

Abstract: A computing device comprising a processor, the processor configured to: receive, from an image capture system, an image captured in an environment and image metadata associated with the image, the image metadata comprising an image capture time; receive a sound recognition message from a sound recognition module, the sound recognition message comprising (i) a sound recognition identifier indicating a target sound or scene that has been recognised based on captured audio data captured in the environment, and (ii) time information associated with the sound recognition identifier; detect that the target sound or scene occurred at a time that the image was captured based on the image metadata and the time information in the sound recognition message; and output a camera control command to said image capture system based on said detection.

Abstract: A computing device, the computing device comprising a processor configured to: receive audio information relating to one or more non-verbal sounds captured by a microphone in an environment of a user; receive motion information that is based on motion sensor data captured by a motion sensor, said motion information relating to motion of said user in the environment; process the audio information and the motion information to recognise an activity of said user; and output an activity recognition notification indicating said activity.

Abstract: A device or system is provided which is configured to detect one or more sound events and/or scenes associa ted with a predetermined context, and to provide an assistive output on fulfilment of that context.

Abstract: Sound detection and identification leads to responsiveness within an augmented reality environment. Information about an identified sound can be converted into a command for implementation by an augmented reality system, for display of a desired on-screen augmented reality effect.

Abstract: Control of navigation of a content item is carried out by detection of non-verbal sound events. On the basis of receipt of one or more non-verbal sound event reports, a navigation tool is provided with a corresponding sequence of navigation commands. The correspondence between navigation command sequences and non-verbal sound events is established through analysis or markup of the content item.

Abstract: A computing device for controlling a user interface of the computing device, the computing device comprising a processor configured to: detect at least one target sound in a monitored environment; determine an operating mode of the computing device that is associated with the at least one target sound; output content, via the user interface of the computing device, that is associated with the operating mode, wherein the content prompts a user of the computing device to perform an action using an input device of the computing device to instruct the computing device to control its own display in the monitored environment in response to the recognition of the at least one target sound.

Abstract: Verification of presence of a detected target is carried out following an initial presence determination on the basis of detected non-verbal sound.

Abstract: A computing device for controlling a user interface of the computing device, the computing device comprising a processor configured to: detect at least one target sound in a monitored environment; determine an operating mode of the computing device that is associated with the at least one target sound; output content, via the user interface of the computing device, that is associated with the operating mode, wherein the content prompts a user of the computing device to perform an action using an input device of the computing device to instruct the computing device to control a controllable device in the monitored environment in response to the recognition of the at least one target sound.

Abstract: A method for generating a health indicator for at least one person of a group of people, the method comprising: receiving, at a processor, captured sound, where the captured sound is sound captured from the group of people; comparing the captured sound to a plurality of sound models to detect at least one non-speech sound event in the captured sound, each of the plurality of sound models associated with a respective health-related sound type; determining metadata associated with the at least one non-speech sound event; assigning the at least one non-speech sound event and the metadata to at least one person of the group of people; and outputting a message identifying the at least one non-speech event and the metadata to a health indicator generator module to generate a health indicator for the at least one person to whom the at least one non-speech sound event is assigned.

Abstract: Broadly speaking, embodiments of the present invention provide a wearable audio device including one or a plurality of microphones, a sound recognition systems and a controller to control the device based on one or more recognized sounds or classes of sound. Embodiments use stored sound models.

Abstract: Broadly speaking, embodiments of the present invention provide a wearable audio device including one or a plurality of microphones, a sound recognition systems and a controller to control the device based on one or more recognised sounds or classes of sound. Embodiments use stored sound models.