Abstract: An intelligent task assistant program can identify tasks associated with a user over a reporting period based on an analysis of, and inferences drawn from, data associated with one or more personal information programs, such as an electronic calendar application, an electronic reminder application, an electronic collaborative application, and/or an electronic communication application. The task assistant may also prioritize the identified tasks based on content associated with the tasks. Some or all of the prioritized tasks can be provided to an output device for perception by the user.

Abstract: Methods, systems, and computer storage media for providing predicted task-actions for tasks from a plurality of task applications associated with a task management system. In operation, a task associated with a task application is accessed at a task-action prediction engine. An intent of the task is determined. The intent of the task is determined based on task features and an intent prediction machine learning model that is trained to predict intents associated with natural language text. Based on the intent of the task, a predicted task-action is selected based on a task-action computation model that is associated with predefined task-actions and predefined intent-task-categories. The predicted task-action can be communicated to a task management client that causes display of the predicted task-action in combination with a predicted task-action interface element associated with executing the predicted task-action.

Abstract: An intelligent task assistant program can identify tasks associated with a user over a reporting period based on an analysis of, and inferences drawn from, data associated with one or more personal information programs, such as an electronic calendar application, an electronic reminder application, an electronic collaborative application, and/or an electronic communication application. The task assistant may also prioritize the identified tasks based on content associated with the tasks. Some or all of the prioritized tasks can be provided to an output device for perception by the user.

Abstract: Systems are configured for generating text-to-speech data in a personalized voice by training a neural text-to-speech machine learning model on natural speech data collected from a particular user, validating the identity of the user from which data is collected, and authorizing requests from users to use the personalized voice in generating new speech data. The systems are further configured to train a machine learning model as a neural text-to-speech model with generated personalized speech data.

Abstract: An intelligent task assistant program can identify tasks associated with a user over a reporting period based on an analysis of, and inferences drawn from, data associated with one or more personal information programs, such as an electronic calendar application, an electronic reminder application, an electronic collaborative application, and/or an electronic communication application. The task assistant may also prioritize the identified tasks based on content associated with the tasks. Some or all of the prioritized tasks can be provided to an output device for perception by the user.