Abstract: A data processing apparatus includes input circuitry to receive audio data for a plurality of respective dialogue recordings for a video game, classification circuitry comprising one or more machine learning models to receive at least a portion of the audio data for each dialogue recording and trained to output classification data indicative of a quality classification of a dialogue recording in dependence upon one or more properties of the audio data for the dialogue recording, and storage circuitry to store identification data for one or more of the plurality of dialogue recordings in dependence upon the classification data.

Abstract: A projector system includes two free-standing, upright projector housings between which a person can be positioned and can be imaged by one or more sensors on each housing. A projector on each housing projects an avatar of the person onto a wall between the projector housings so that the person can view his avatar.

Abstract: A system for generating a head-related transfer function, HRTF, dataset, the system comprising an HRTF dataset selection unit operable to select two or more HRTF datasets, a characteristic identification unit operable to identify characteristics of the selected HRTF datasets, an HRTF dataset modification unit operable to modify one or more elements of the one or more selected HRTF datasets in dependence upon deviations in identified characteristics of the HRTF datasets, and an HRTF dataset generation unit operable to generate a combined HRTF dataset comprising at least the modified HRTF elements.

Abstract: A data processing apparatus adapted to generate a recording for a content includes: input circuitry configured to obtain image data and corresponding audio data for the content, the image data including a plurality of image frames, a plurality of machine learning models including one or more first machine learning models and one or more second machine learning models, each first machine learning model configured to obtain at least a part of the image data and trained to output respective indicator data for the plurality of image frames, each second machine learning model configured to obtain at least a part of the audio data and trained to output respective indicator data for the plurality of image frames corresponding to the at least part of the audio data, where the respective indicator data associated with an image frame is indicative of an interest score for the image frame, authoring circuitry configured to select one or more groups of image frames from the plurality of image frames in dependence upon re

Abstract: A system for determining prioritisation values for two or more sounds within an audio clip includes: a feature extraction unit operable to extract characteristic features from the two or more sounds, a feature combination unit operable to generate a combined mix comprising extracted features from the two or more sounds, an audio assessment unit operable to identify the contribution of one or more of the features to the combined mix, a feature classification unit operable to assign a saliency score to each of the features in the combined mix, and an audio prioritisation unit operable to determine relative priority values for the two or more sounds in dependence upon the assigned saliency scores for each of one or more features of the sounds.

Abstract: A method of obtaining a head-related transfer function for a user is provided. The method comprises generating an audio signal for output by a handheld device and outputting the generated audio signal at a plurality of locations by moving the handheld device to those locations. The audio output by the handheld device is detected at left-ear and right-ear microphones. A pose of the handheld device relative to the user's head is determined for at least some of the locations. One or more personalised HRTF features are then determined based on the detected audio and corresponding determined poses of the handheld device. The one or more personalised HRTF features are then mapped to a higher-quality HRTF for the user, wherein the higher-quality HRTF corresponds to an HRTF measured in an anechoic environment. This mapping may be learned using machine learning, for example. A corresponding system is also provided.

Abstract: A system for generating audio content in dependence upon an input audio track comprising audio corresponding to one or more sound sources, the system comprising an audio input unit operable to input the input audio track to one or more models, each representing one or more of the sound sources, and an audio generation unit operable to generate, using the one or more models, one or more audio tracks each comprising a representation of the audio contribution of the corresponding sound sources of the input audio track, wherein the generated audio tracks comprise one or more variations relative to the corresponding portion of the input audio track.

Abstract: A system for generating a head-related transfer function, HRTF, dataset, the system comprising an HRTF dataset selection unit operable to select two or more HRTF datasets, a characteristic identification unit operable to identify characteristics of the selected HRTF datasets, an HRTF dataset modification unit operable to modify one or more elements of the one or more selected HRTF datasets in dependence upon deviations in identified characteristics of the HRTF datasets, and an HRTF dataset generation unit operable to generate a combined HRTF dataset comprising at least the modified HRTF elements.

Abstract: A system for generating a head-related transfer function, HRTF, for a given position with respect to a listener, the system comprising a dividing unit operable to divide each of a plurality of existing HRTFs, each corresponding to a respective plurality of positions, into first and second components, an interaural time difference determination unit operable to determine an interaural time difference expected by a user for a sound source located at the given position in dependence upon the respective first components, an interpolation unit operable to generate an interpolated second component by interpolating generated second components using a weighting dependent upon the respective positions for the corresponding HRFTs and the given position, and a generation unit operable to generate an HRTF for the given position in dependence upon the interaural time difference and the interpolated second component.