Abstract: Techniques performed by a data processing system for processing voice content received from a user herein include receiving a first audio input from a user comprising spoken content, analyzing the first audio input using one or more natural language processing models to produce a first textual output comprising a textual representation of the first audio input, analyzing the first textual output using one or more machine learning models to determine first context information of the first textual output, and processing the first textual output in the application based on the first context information.

Abstract: Techniques performed by a data processing system for processing voice content received from a user herein include receiving a first audio input from a user comprising spoken content, analyzing the first audio input using one or more natural language processing models to produce a first textual output comprising a textual representation of the first audio input, analyzing the first textual output using one or more machine learning models to determine first context information of the first textual output, and processing the first textual output in the application based on the first context information.

Abstract: A system and method for personalizing a display of a recommendation in a user interface element of an application is described. The system accesses application activities of a user of the application. A user preference is formed based on the application activities. The system identifies a context of a current activity of the application and generates a content recommendation in the application based on the context of the current activity of the application and the user preference.

Abstract: A computer-implemented technique is described herein for removing sensitive content from documents in a manner that preserves the usefulness of the documents for subsequent analysis. For instance, the technique obscures sensitive content in the documents, while retaining meaningful information in the documents for subsequent processing by a machine-learning engine or other machine-implemented analysis mechanisms. According to one illustrative aspect, the technique removes sensitive content from documents using a modification strategy that is chosen based on one or more selection factors. One selection factor pertains to the nature of the processing that is to be performed on the documents after they have been anonymized.

Abstract: A computer-implemented technique is described herein for removing sensitive content from documents in a manner that preserves the usefulness of the documents for subsequent analysis. For instance, the technique obscures sensitive content in the documents, while retaining meaningful information in the documents for subsequent processing by a machine-learning engine or other machine-implemented analysis mechanisms. According to one illustrative aspect, the technique removes sensitive content from documents using a modification strategy that is chosen based on one or more selection factors. One selection factor pertains to the nature of the processing that is to be performed on the documents after they have been anonymized.