Abstract: A media edit point selection process can include a media editing software application programmatically converting speech to text and storing a timestamp-to-text map. The map correlates text corresponding to speech extracted from an audio track for the media clip to timestamps for the media clip. The timestamps correspond to words and some gaps in the speech from the audio track. The probability of identified gaps corresponding to a grammatical pause by the speaker is determined using the timestamp-to-text map and a semantic model. Potential edit points corresponding to grammatical pauses in the speech are stored for display or for additional use by the media editing software application. Text can optionally be displayed to a user during media editing.

Abstract: A media edit point selection process can include a media editing software application programmatically converting speech to text and storing a timestamp-to-text map. The map correlates text corresponding to speech extracted from an audio track for the media clip to timestamps for the media clip. The timestamps correspond to words and some gaps in the speech from the audio track. The probability of identified gaps corresponding to a grammatical pause by the speaker is determined using the timestamp-to-text map and a semantic model. Potential edit points corresponding to grammatical pauses in the speech are stored for display or for additional use by the media editing software application. Text can optionally be displayed to a user during media editing.

Abstract: A media edit point selection process can include a media editing software application programmatically converting speech to text and storing a timestamp-to-text map. The map correlates text corresponding to speech extracted from an audio track for the media clip to timestamps for the media clip. The timestamps correspond to words and some gaps in the speech from the audio track. The probability of identified gaps corresponding to a grammatical pause by the speaker is determined using the timestamp-to-text map and a semantic model. Potential edit points corresponding to grammatical pauses in the speech are stored for display or for additional use by the media editing software application. Text can optionally be displayed to a user during media editing.

Abstract: In implementations of proficiency based tutorial modification, a computing device implements a tutorial system to receive a user modification of a digital image. A difference between the user modification and an application modification of the digital image is determined. The tutorial system generates a proficiency score for an editing tool based on the difference between the user modification and the application modification, and the proficiency score indicates the user's proficiency in using the editing tool. The tutorial system generates a pre-modified input image for a tutorial depicting a modification applied to an input image to be modified in the tutorial using the editing tool based on the proficiency score for the editing tool being greater than a proficiency threshold.

Abstract: In implementations of proficiency based tutorial modification, a computing device implements a tutorial system to receive a user modification of a digital image. A difference between the user modification and an application modification of the digital image is determined. The tutorial system generates a proficiency score for an editing tool based on the difference between the user modification and the application modification, and the proficiency score indicates the user's proficiency in using the editing tool. The tutorial system generates a pre-modified input image for a tutorial depicting a modification applied to an input image to be modified in the tutorial using the editing tool based on the proficiency score for the editing tool being greater than a proficiency threshold.

Abstract: Techniques of detecting edges of objects in images include applying an adaptive threshold to a sigmoidal membership function of a fuzzy gradient of the image brightness. For example, when a computer configured to detect edges of an object of an image receives a grayscale image, the computer computes gradients of the image brightness at each pixel to form a gradient matrix. The computer then creates a fuzzy gradient matrix by applying a sigmoidal membership function to each element of the gradient matrix to form a smoothed gradient matrix. The computer then performs an adaptive threshold operation on the smoothed gradient matrix to produce the edges of the object of the image.

Abstract: Techniques of detecting edges of objects in images include applying an adaptive threshold to a sigmoidal membership function of a fuzzy gradient of the image brightness. For example, when a computer configured to detect edges of an object of an image receives a grayscale image, the computer computes gradients of the image brightness at each pixel to form a gradient matrix. The computer then creates a fuzzy gradient matrix by applying a sigmoidal membership function to each element of the gradient matrix to form a smoothed gradient matrix. The computer then performs an adaptive threshold operation on the smoothed gradient matrix to produce the edges of the object of the image.