Dynamic system and method for content and topic based synchronization during presentations

Abstract

Disclosed embodiments provide techniques for automatically synchronizing a visual presentation with a live presenter, Visual presentation slides are preprocessed to determine one or more topics for each slide. A topic index contains one or more topics corresponding to slides of the presentation. As a presenter provides a verbal presentation for corresponding slides, natural language processing analyzes the verbal presentation and creates one or more temporal verbal topic categories. The temporal verbal topic categories are used to search the topic index to find one or more slides that best match the current temporal verbal topic categories. In this way, the slides can automatically follow the discussion of the presenter, enabling improved presentations that can enhance the user experience, increase audience engagement, and improve the dissemination of information.

1 . A computer-implemented method for automatic synchronization of a visual presentation comprising a plurality of slides with a verbal presentation, comprising:
 performing a computer-generated topic analysis for each slide of the plurality of slides;   creating a topic index for the visual presentation, wherein the topic index comprises an entry for each slide, wherein each entry includes one or more topic keywords associated therewith;   performing a real-time computerized natural language analysis of the verbal presentation;   deriving one or more temporal verbal topic categories from the real-time computerized natural language analysis;   searching the topic index for a best matching entry, based on the one or more temporal verbal topic categories; and   rendering a slide from the plurality of slides that corresponds to the best matching entry.   
     
     
         2 . The method of  claim 1 , wherein performing a computer-generated topic analysis for each slide comprises performing a computerized natural language processing analysis of each slide of the plurality of slides. 
     
     
         3 . The method of  claim 1 , wherein performing a computer-generated topic analysis includes performing an image analysis for an image within a slide from the plurality of slides. 
     
     
         4 . The method of  claim 1 , wherein performing a computerized natural language analysis comprises:
 performing an entity detection process on text data from one or more slides from the plurality of slides;   deriving a topic based on each entity detected from the entity detection process; and   recording the derived topic and corresponding slide in the topic index.   
     
     
         5 . The method of  claim 4 , further comprising:
 detecting a second best matching entry; and   rendering the slide from the plurality of slides that corresponds to the second best matching entry adjacent to the slide that corresponds to the best matching entry.   
     
     
         6 . The method of  claim 2 , wherein performing a computerized natural language analysis comprises performing a long word analysis. 
     
     
         7 . The method of  claim 2 , wherein performing a computerized natural language analysis comprises performing a dispersion analysis. 
     
     
         8 . The method of  claim 2 , wherein performing a computerized natural language analysis comprises performing a bigram analysis. 
     
     
         9 . The method of  claim 2 , wherein performing a computerized natural language analysis process comprises using a naive Bayes classifier. 
     
     
         10 - 20 . (canceled)