| CPC G06F 40/30 (2020.01) [G06F 40/10 (2020.01); G06F 40/279 (2020.01); G06F 40/58 (2020.01); G06N 3/08 (2013.01); G10L 13/02 (2013.01)] | 20 Claims |

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1. A computer-implemented method comprising:
obtaining text-based data and non-text-based data associated with at least one virtual event comprising one or more participants, wherein obtaining text-based data and non-text-based data comprises converting at least a portion of the non-text-based data to at least a portion of the text-based data by converting at least a portion of at least one image, corresponding to presentation materials within the at least one virtual event, to text using at least one mask region-based convolutional neural network (mask R-CNN) model in connection with one or more segmentation techniques, wherein the at least one mask R-CNN model comprises a multi-task network trained to predict at least one text localization output and at least one text recognition output from a same portion of the at least one image;
generating a content-related summarization of one or more of at least a portion of the text-based data and at least a portion of the non-text-based data using at least a first set of one or more artificial intelligence techniques;
generating a participant sentiment-related summarization associated with one or more of at least a portion of the text-based data and at least a portion of the non-text-based data using at least a second set of one or more artificial intelligence techniques; and
performing one or more automated actions based at least in part on one or more of the content-related summarization and the participant sentiment-related summarization;
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.
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