Patent ID: 11949971
Assignee: PRIME FOCUS TECHNOLOGIES LIMITED
Field: Audio-visual technology (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 0:
1. A system for automatically identifying key dialogues in a media asset, the system comprising:
at least one processor;
a non-transitory, computer-readable storage medium operably and communicatively coupled to the at least one processor and configured to store the media asset and computer program instructions executable by the at least one processor; and
a key dialogues engine configured to define the computer program instructions, which when executed by the at least one processor, cause the at least one processor to:
receive the media asset and extract characteristic data from the media asset, wherein the characteristic data comprises transcript data and supplementary data;
process the transcript data into a plurality of transcript data elements and associate the transcript data elements with respective data elements selected from the supplementary data; and
identify one or more key dialogues from the associated transcript data elements based on configurable criteria, in operable communication with one or more of a plurality of data sources, wherein the configurable criteria comprise one or more of repetitive keywords, rhyming words, audio signal levels, matching keywords, text-based sentiments, dialogue similarity, repetitive dialogues, signature dialogues, entry dialogues recited by actors comprising protagonists and antagonists, faces of the actors, celebrity detection, image labels, and vector similarity scores;, Characterized in that:
wherein the supplementary data comprises at least one of image label data and face recognition data, and wherein the at least one processor is configured to divide the transcript data into a plurality of sentence data elements, and to associate each of the sentence data elements with respective image label data and face recognition data in accordance with time codes of the sentence data elements, during the processing of the transcript data;
wherein the at least one processor is configured to generate a comprehensive database from the plurality of data sources, and wherein the comprehensive database is configured to store a plurality of keywords, rhyming words, dialogues, image labels, text-based sentiments, face data of actors, image label data, and information of actors selected from a plurality of media assets;
wherein the at least one processor is configured to allocate a weightage to each of the configurable criteria, compute a score for the each of the associated transcript data elements based on the configurable criteria met by the each of associated transcript data elements, and rank the each of the associated transcript data elements based on the computed score,
wherein the at least one processor is configured to determine occurrence of one or more key audio events proximal to each of the associated transcript data elements based on the audio signal levels of the media asset, for identifying the one or more key dialogues from the associated transcript data elements based on the audio signal levels;
wherein the at least one processor is configured to classify each of the associated transcript data elements as one of positive, negative, and neutral, and compute a probability for the each of the associated transcript data elements, for identifying the one or more key dialogues from the associated transcript data elements based on the text-based sentiments;
wherein the at least one processor is configured to generate vectors for the associated transcript data elements, compute a vector similarity score defining a similarity between each of the vectors, store the vector similarity score of the each of the associated transcript data elements in a similarity matrix, and convert the similarity matrix into a graphical representation for computation of a rank of the each of the associated transcript data elements, for identifying the one or more key dialogues from the associated transcript data elements.