Abstract: A method modifies and utilizes a text document based on an audio file that has captured audio proceedings relevant to the text document. One or more processors and/or a user segment the text document into topic-based text segments. Processor(s) receive an audio file that is relevant to the text document, convert the audio file into text, and match a specific topic-based text segment from the topic-based text segments to a specific topic-based audio segment from the topic-based audio segments. In response to identifying a difference between content in the specific topic-based text segment and content in the specific topic-based audio segment, processor(s) and/or the user update the specific topic-based text segment with the content in the specific topic-based audio segment to create an updated version of the text document.

Abstract: A method modifies and utilizes a text document based on an audio file that has captured audio proceedings relevant to the text document. One or more processors and/or a user segment the text document into topic-based text segments. Processor(s) receive an audio file that is relevant to the text document, convert the audio file into text, and match a specific topic-based text segment from the topic-based text segments to a specific topic-based audio segment from the topic-based audio segments. In response to identifying a difference between content in the specific topic-based text segment and content in the specific topic-based audio segment, processor(s) and/or the user update the specific topic-based text segment with the content in the specific topic-based audio segment to create an updated version of the text document.

Abstract: Aspects extend to methods, systems, and computer program products for predicting events from aggregated device sensed physical data. Aspects facilitate dynamically targeted collection and aggregation of physical metrics (e.g., body metrics and environmental metrics) from varying sensing devices. Aggregated data can be used for pattern analysis, reporting and predictive results on health related events (or other scenarios). Collected physical metric data can be anonymized or personalized based at least in part on data source. Pattern analysis can be used to report at different levels (e.g., personal or commercial, localized or global) and return relevant contextual driven results, including potential healthcare related events or other events relating to the study of changes that occur in large groups of people over a period of time (e.g., relating to demography).