Machine learning multimedia conversion assignment

A computer program product, comprising a computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a processor of a server hardware device implements a machine learning multimedia conversion improvement method, said method comprising:

• automatically connecting, by said processor, hardware devices to said server hardware device;
• recording, by said processor from an audio or video conference at a geographical location, audio and/or video data from a meeting between a plurality of individuals;
• identifying, by said processor executing a plurality of automated sensors, each individual of plurality of individuals;
• identifying, by said processor via sensors or external sources, attributes of each said individual;
• converting, by said processor, said audio and/or video data to associated text data;
• associating, by said processor, portions of said text data with associated individuals of said plurality of individuals;
• analyzing, by said processor, said portions of said text data;
• identifying, by said processor based on results of said analyzing, action items identified in said text data;
• assigning, by said processor, said action items to said plurality of individuals based on identified attributes;
• generating, by said processor based on results of said assigning, self-learning software code for executing future multimedia conversion processes;
• and
• modifying, by said processor based on results of executing said future multimedia conversion processes, said self-learning software code.

A server hardware device comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a machine learning multimedia conversion improvement method comprising:

• automatically connecting, by said processor, hardware devices to said server hardware device;
• recording, by said processor from an audio or video conference at a geographical location, audio and/or video data from a meeting between a plurality of individuals;
• identifying, by said processor executing a plurality of automated sensors, each individual of plurality of individuals;
• identifying, by said processor via sensors or external sources, attributes of each said individual;
• converting, by said processor, said audio and/or video data to associated text data;
• associating, by said processor, portions of said text data with associated individuals of said plurality of individuals;
• analyzing, by said processor, said portions of said text data;
• identifying, by said processor based on results of said analyzing, action items identified in said text data;
• assigning, by said processor, said action items to said plurality of individuals based on identified attributes;
• generating, by said processor based on results of said assigning, self-learning software code for executing future multimedia conversion processes;
• and
• modifying, by said processor based on results of executing said future multimedia conversion processes, said self-learning software code.