Method and system for self-correcting match states

A system for predicting a match state event by a machine learning platform on a server, the system comprising:

• a communication unit that includes a transmitter and a receiver, the receiver being arranged to receive a live data feed;
• a match state collector that includes a memory arranged to store match state data;
• an anomaly predictor having a machine learning system arranged to
• monitor multimedia content on the live data feed,
• receive current match state data that is based on a current state of a live match and that corresponds to the multimedia content, and
• predict, by a machine learning platform, accuracy of the multimedia content based on the multimedia content and corresponding match state data, utilizing one or more specialized neural network models trained to interpret the multimedia content;
• and
• an error corrector having a computing device arranged to resolve an anomaly in the multimedia content based on the predicted accuracy of the multimedia content, wherein resolving the anomaly includes (i) encoding a portion of the multimedia content containing the predicted anomaly, (ii) storing the serialized anomaly and a corresponding serialized function that specifies how to resolve the anomaly, and (iii) executing the serialized function based on the serialized anomaly, wherein executing the serialized function causes extracting a portion of the multimedia content containing the anomaly, ignoring the anomaly, or correcting the anomaly;
• and
• a match state predictor having a machine learning event (MLE) model arranged to predict a future match state based on the current match state data and the multimedia content, including the resolved anomaly,
• wherein the transmitter is configured to send the future match state to a communicating device.

A non-transitory computer-readable storage medium containing computer executable instructions that, when executed by a computing device coupled to a communication unit having a transmitter and a receiver and containing a machine learning system, cause the computing device to perform operations comprising:

• receiving, by the receiver, a live data feed;
• monitoring, by the machine learning system, multimedia content on the received live data feed;
• receiving, from a memory coupled to the computing device, current match state data corresponding to the multimedia content, the current match state data being based on a current state of a live match;
• predicting, by the machine learning system, an anomaly in the multimedia content based on an analysis of received multimedia content and the current match state data, wherein the analysis utilizes one or more specialized neural network model trained to interpret the multimedia content;
• resolving, by the machine learning system, the predicted anomaly by (i) encoding a portion of the multimedia content containing the predicted anomaly, (ii) storing the serialized anomaly and a corresponding serialized function that specifies how to resolve the anomaly, and (iii) executing the serialized function based on the serialized anomaly, wherein executing the serialized function causes:
• extracting a portion of the multimedia content containing the anomaly, ignoring the anomaly, or correcting the anomaly;
• predicting, by the machine learning system, a future match state based on the current match state data and the multimedia content, including the resolved anomaly;
• and
• sending, by the transmitter, the future match state to a communicating device.