Abstract: Techniques for providing adaptive assistive technology for assisting users with visual impairment can be used on a computing device. These techniques include displaying content to a user, capturing a series of images or video of the user using a camera, analyzing the series of images or video to determine whether the user is exhibiting behavior or characteristics indicative of visual impairment, and rendering a magnification user interface on the display configured to magnify at least a portion of the content of the display based on a determination that the user is exhibiting behavior or characteristics indicative of visual impairment. The magnification user interface may be controlled based on head and/or eye movements of the user of the computing device.

Abstract: Techniques for providing adaptive assistive technology for assisting users with visual impairment can be used on a computing device. These techniques include displaying content to a user, capturing a series of images or video of the user using a camera, analyzing the series of images or video to determine whether the user is exhibiting behavior or characteristics indicative of visual impairment, and rendering a magnification user interface on the display configured to magnify at least a portion of the content of the display based on a determination that the user is exhibiting behavior or characteristics indicative of visual impairment. The magnification user interface may be controlled based on head and/or eye movements of the user of the computing device.

Abstract: Techniques for providing adaptive assistive technology for assisting users with visual impairment can be used on a computing device. These techniques include displaying content to a user, capturing a series of images or video of the user using a camera, analyzing the series of images or video to determine whether the user is exhibiting behavior or characteristics indicative of visual impairment, and rendering a magnification user interface on the display configured to magnify at least a portion of the content of the display based on a determination that the user is exhibiting behavior or characteristics indicative of visual impairment. The magnification user interface may be controlled based on head and/or eye movements of the user of the computing device.

Abstract: Techniques for providing adaptive assistive technology for assisting users with visual impairment can be used on a computing device. These techniques include displaying content to a user, capturing a series of images or video of the user using a camera, analyzing the series of images or video to determine whether the user is exhibiting behavior or characteristics indicative of visual impairment, and rendering a magnification user interface on the display configured to magnify at least a portion of the content of the display based on a determination that the user is exhibiting behavior or characteristics indicative of visual impairment. The magnification user interface may be controlled based on head and/or eye movements of the user of the computing device.

Abstract: Adaptive assistance technologies can assist a user with operating a computing device. A method according to these techniques includes analyzing user interactions with the computing device, determining that the user interactions with the computing device are indicative of a user experiencing one or more issues for which adaptive assistive technologies provided by the computing device may assist the user, identifying one or more assistive technologies provided by the computing device that may address the one or more issues, modifying one or more operating parameters of the computing device using the one or more assistive technologies, and operating the computing device according to the one or more modified operating parameters.

Abstract: Quick tasks for on-screen keyboards are described in which an on-screen keyboard supports a plurality of quick tasks configured to edit selected text in defined ways. Quick task functions may be assigned to keys of the on-screen keyboard in addition to the default actions or “normal” character entry functions of the keys. During text input, the keys operate normally to perform a function related to character entry, such as to cause input of corresponding text character. When text is selected or in other designated interaction scenarios, operation of a key associated with a quick task may automatically trigger the quick task to modify selected text in a corresponding way. Thus, the same key of an on-screen keyboard may be employed to initiate a function related to character entry or apply of a quick task to text depending upon the interaction scenario.

Abstract: Methods, systems, and apparatuses in a computing device enable magnification of selectable display objects. A first interaction event associated with a first selectable display object displayed in a display screen, the display screen having a boundary and a current magnification level is detected. A first display location and a first unmagnified size of the first selectable display object in the display screen is determined and a magnified display size for the first selectable display object based at least on the first unmagnified size is determined. A second display location for the first selectable display object based at least on the first display location is determined and the first selectable display object is displayed at the magnified display size and at the second display location on the display screen. The display screen is otherwise displayed entirely at the current magnification level.

Abstract: Techniques to employ emoji for text predictions are described herein. In one or more implementations, entry of characters is detected during interaction with a device. Prediction candidates corresponding to the detected characters are generated according to a language model that is configured to consider emoji along with words and phrases. The language model may make use of a mapping table that maps a plurality of emoji to corresponding words. The mapping table enables a text prediction engine to offer the emoji as alternatives for matching words. In addition or alternatively, the text prediction engine may be configured to analyze emoji as words within the model and generate probabilities and candidate rankings for predictions that include both emoji and words. User-specific emoji use may also be learned by monitoring a user's typing activity to adapt predictions to the user's particular usage of emoji.

Abstract: Quick tasks for on-screen keyboards are described in which an on-screen keyboard supports a plurality of quick tasks configured to edit selected text in defined ways. Quick task functions may be assigned to keys of the on-screen keyboard in addition to the default actions or “normal” character entry functions of the keys. During text input, the keys operate normally to perform a function related to character entry, such as to cause input of corresponding text character. When text is selected or in other designated interaction scenarios, operation of a key associated with a quick task may automatically trigger the quick task to modify selected text in a corresponding way. Thus, the same key of an on-screen keyboard may be employed to initiate a function related to character entry or apply of a quick task to text depending upon the interaction scenario.

Abstract: Techniques are described to generate text prediction candidates corresponding to detected text characters according to an adaptive language model that includes multiple individual language model dictionaries. Respective scoring data from the dictionaries is combined to select prediction candidates in different interaction scenarios. In an implementation, dictionaries corresponding to multiple different languages are combined to produce multi-lingual predictions. Predictions for different languages may be weighted proportionally according to relative usage by a user. Weights used to combine contributions from multiple dictionaries may also depend upon factors such as how recently a word is used, number of times used, and so forth. Further, the dictionaries may include interaction-specific dictionaries that are learned by monitoring a user's typing activity to adapt predictions to corresponding usage scenarios.

Abstract: Assistive buffer usage techniques are described. In one or more implementations, audio generated through text-to-speech conversion is output, the audio corresponding to text portioned in one of a plurality of buffers from an item of content. An input is received to rewind or fast forward the output of the audio. Responsive to the input, additional audio is output that was generated through text-to-speech conversion from text portioned in another one of the plurality of buffers.

Abstract: Assistive buffer usage techniques are described. In one or more implementations, audio generated through text-to-speech conversion is output, the audio corresponding to text portioned in one of a plurality of buffers from an item of content. An input is received to rewind or fast forward the output of the audio. Responsive to the input, additional audio is output that was generated through text-to-speech conversion from text portioned in another one of the plurality of buffers.