Abstract: Broadly speaking, the present disclosure relates to a computer-implemented method for training a machine learning, ML, automatic speech recognition, ASR, model. The method comprises injecting a speaker anonymiser, which is configured to cause the ML ASR model to generate anonymised acoustic embeddings for the ML ASR model, at one or more layers of the ML ASR model, and suitably training the ML ASR model including the speaker anonymiser on audio data comprising an utterance with one or more words to be recognised. Correspondingly, there is also described a computer implemented method for performing automatic speech recognition using the trained ML ASR model and system for training/inference thereof.

Abstract: A method of obtaining a patched signal for training a model for use in at least one of a speech and an audio recognition is disclosed. The method comprises obtaining a first signal, wherein the first signal is at least one of a speech and an audio signal, modifying the first signal to obtain at least one second signal, dividing the first signal and the at least one second signal respectively into a plurality of first patches and a plurality of second patches, wherein each one of the plurality of first patches comprises a respective part of the first signal and each one of the plurality of second patches comprises a respective part of the at least one second signal and mixing selected ones of the plurality of first patches and the plurality of second patches to obtain a patched signal.

Abstract: Image processing comprises receiving content from an application; rendering the content into a rendered frame and storing the rendered frame in a frame buffer; transferring the rendered frame from the frame buffer to a compositor, and displaying the rendered frame using the compositor. The image processing further comprises applying a non-linear transformation to at least part of the rendered frame during the rendering the content into the rendered frame; during the transferring of the rendered frame to the compositor, or during the displaying of the rendered frame by the compositor.

Abstract: A method of setting operating system parameters of a device includes: identifying, based on execution of an application, at least one workload type for the application; generating a workload-specific policy corresponding to the at least one workload type; and setting the operating system parameters based on the workload-specific policy.

Abstract: A method of setting operating system parameters of a device includes: identifying, based on execution of an application, at least one workload type for the application; generating a workload-specific policy corresponding to the at least one workload type; and setting the operating system parameters based on the workload-specific policy.

Abstract: An image processing method is provided. The image processing method includes detecting a face of an object present on an image, obtaining at least one feature from the detected face as at least one facial parameter and obtaining at least one context related to the image as at least one contextual parameter, determining a manipulation point for manipulating the detected face, based on the obtained at least one facial parameter and the obtained at least one contextual parameter, and manipulating the image based on the determined manipulation point.

Abstract: Provided is a method of managing power of an electronic device. The method includes: obtaining operation information related to an operation from among operations performed by the electronic device. The operation is recognizable to a user via a product of hardware processing performed by hardware included in the electronic device. The method also includes obtaining load information related to a load generated by the operation performed by the electronic device. In addition, the method includes performing power management on the hardware included in the electronic device based on the operation information and the load information.

Abstract: Provided is a method of managing power of an electronic device. The method includes: obtaining operation information related to an operation from among operations performed by the electronic device. The operation is recognizable to a user via a product of hardware processing performed by hardware included in the electronic device. The method also includes obtaining load information related to a load generated by the operation performed by the electronic device. In addition, the method includes performing power management on the hardware included in the electronic device based on the operation information and the load information.