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: 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 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 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.

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.