Abstract: Techniques are described for generating HLSD for a textual format source code, which, when rendered, causes a display of visual content. The rendering of the source code generates a tree hierarchy of visual source elements, which logically is possible to map to any graph tree. In an embodiment, visual source elements of the source code are classified to higher-level semantic data (HLSD) labels based on their property(s) and/or the property(s) of neighbor visual source element(s) in the tree hierarchy (context). The HLSD labels indicate the type of HLSD widget mapped to the visual source elements. Techniques further include determining features and a layout arrangement for HLSD widgets and generating a template thereof for the visual content.

Abstract: Example speech enhancement and noise suppression systems and methods are described. In one implementation, a method receives an audio file comprising a combination of voice data and noise data, and divides the audio file into multiple frames. The method performs a discrete Fourier transform on each frame of a first subset of the multiple frames to provide a plurality of frequency-domain outputs, which are input to a neural network. A ratio mask is obtained as an output from the neural network and clean voice coefficients are computed using the ratio mask. The method outputs an audio file having enhanced speech based on the computed clean voice coefficients.

Abstract: Techniques are described for generating HLSD for a textual format source code, which, when rendered, causes a display of visual content. The rendering of the source code generates a tree hierarchy of visual source elements, which logically is possible to map to any graph tree. In an embodiment, visual source elements of the source code are classified to higher-level semantic data (HLSD) labels based on their property(s) and/or the property(s) of neighbor visual source element(s) in the tree hierarchy (context). The HLSD labels indicate the type of HLSD widget mapped to the visual source elements. Techniques further include determining features and a layout arrangement for HLSD widgets and generating a template thereof for the visual content.

Abstract: Example speech enhancement and noise suppression systems and methods are described. In one implementation, a method receives an audio file comprising a combination of voice data and noise data, and divides the audio file into multiple frames. The method performs a discrete Fourier transform on each frame of a first subset of the multiple frames to provide a plurality of frequency-domain outputs, which are input to a neural network. A ratio mask is obtained as an output from the neural network and clean voice coefficients are computed using the ratio mask. The method outputs an audio file having enhanced speech based on the computed clean voice coefficients.