Abstract: A method of detecting occurrences of a sound event in an audio signal comprising a sequence of frames of audio data, each frame corresponding to a respective time in the audio signal, the method comprising: for each frame in the sequence: determining, using the audio data of the frame, a first conditional probability value that a transition occurred from a sound event not having started to the sound event being ongoing, and a second conditional probability value that a transition occurred from a sound event being ongoing to the sound event having ended; and determining a marginal probability value that a sound event was ongoing at the time corresponding to the frame, the marginal probability value being determined using the first and second conditional probability values for the frame and a previously determined marginal probability value that a sound event was ongoing at a time corresponding to a frame preceding the frame in the sequence.

Abstract: A method for recognising at least one of a non-verbal sound event and a scene in an audio signal comprising a sequence of frames of audio data, the method comprising: for each frame of the sequence: processing the frame of audio data to extract multiple acoustic features for the frame of audio data; and classifying the acoustic features to classify the frame by determining, for each of a set of sound classes, a score that the frame represents the sound class; processing the sound class scores for multiple frames of the sequence of frames to generate, for each frame, a sound class decision for each frame; and processing the sound class decisions for the sequence of frames to recognise the at least one of a non-verbal sound event and a scene.

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: 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: 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 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 method, and system, of digital room correction for a device, such as a smart speaker, including a loudspeaker. The method comprises capturing audio from an environment local to the device, for example from one or more microphones of a smart speaker. The captured audio is then processed to recognize one or more categories of sound. A digital room correction procedure may then be controlled dependent upon recognition and/or analysis of at least one of the categories of sound.

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 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, 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 method for recognising at least one of a non-verbal sound event and a scene in an audio signal comprising a sequence of frames of audio data, the method comprising: for each frame of the sequence: processing the frame of audio data to extract multiple acoustic features for the frame of audio data; and classifying the acoustic features to classify the frame by determining, for each of a set of sound classes, a score that the frame represents the sound class; processing the sound class scores for multiple frames of the sequence of frames to generate, for each frame, a sound class decision for each frame; and processing the sound class decisions for the sequence of frames to recognise the at least one of a non-verbal sound event and a scene.

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: 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 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 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: A method for recognising at least one of a non-verbal sound event and a scene in an audio signal comprising a sequence of frames of audio data, the method comprising: for each frame of the sequence: receiving at least one sound class score, wherein each sound class score is representative of a degree of affiliation of the frame with a sound class of a plurality of sound classes; for a sound class score of the at least one sound class scores: determining a confidence that the sound class score is representative of a degree of affiliation of the frame with the sound class by processing a value for a property associated with the frame, wherein the value is processed using a learned model for the property; adjusting the sound class score for the frame based at least on the determined confidence.

Abstract: A method of training a non-verbal sound class detection machine learning system, the non-verbal sound class detection machine learning system comprising a machine learning model configured to: receive data for each frame of a sequence of frames of audio data obtained from an audio signal; for each frame of the sequence of frames: process the data for multiple frames; and output data for at least one sound class score representative of a degree of affiliation of the frame with at least one sound class of a plurality of sound classes, wherein the plurality of sound classes comprises: one or more target sound classes; and a non-target sound class representative of an absence of each of the one or more target sound classes; wherein the method comprises: training the machine learning model using a loss function.