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

Claim 9:
10. A method executed by a key dialogues engine comprising at least one processor for automatically identifying key dialogues in a media asset, the method comprises steps of:
receiving the media asset and extracting characteristic data from the media asset, wherein the characteristic data comprises transcript data and supplementary data;
processing the transcript data into a plurality of transcript data elements and associating the transcript data elements with respective data elements selected from the supplementary data; and
identifying 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;
ranking the each of the associated transcript data elements by the key dialogues engine by:
allocating a weightage to each of the configurable criteria by the key dialogues engine;
computing a score for the each of the associated transcript data elements by the key dialogues engine based on the configurable criteria met by the each of associated transcript data elements; and
assigning a rank to the each of the associated transcript data elements based on the computed score;, Characterized in that:
wherein the supplementary data comprises at least one of image label data and face recognition data, and wherein the processing of the transcript data comprises dividing the transcript data into a plurality of sentence data elements by the key dialogues engine, and associating 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 by the key dialogues engine;
wherein the identification of the one or more key dialogues from the associated transcript data elements based on the audio signal levels comprises determining occurrence of one or more key audio events proximal to each of the associated transcript data elements by the key dialogues engine based on the audio signal levels of the media asset;
wherein the identification of the one or more key dialogues from the associated transcript data elements based on the text-based sentiments comprises classifying each of the associated transcript data elements as one of positive, negative, and neutral, and computing a probability for the each of the associated transcript data elements, by the key dialogues engine;
wherein the identification of the one or more key dialogues from the associated transcript data elements based on the dialogue similarity comprises determining a similarity parameter defining a similarity between each of the associated transcript data elements and each of a plurality of dialogues by the key dialogues engine, wherein the plurality of dialogues is stored in a dialogues database configured as one of the data sources;
wherein the identification of the one or more key dialogues from the associated transcript data elements comprises identifying one or more of repetitive dialogues and signature dialogues in the media asset by the key dialogues engine by executing a probabilistic language model;
wherein the identification of the one or more key dialogues from the associated transcript data elements based on the image labels comprises determining a match in the image labels that are present within time codes of the each of the associated transcript data elements with a predetermined list of image labels by the key dialogues engine, wherein the predetermined list of image labels is stored in an image labels database configured as one of the data sources;
wherein the identification of the one or more key dialogues from the associated transcript data elements comprises:
generating vectors for the associated transcript data elements by the key dialogues engine;
computing a vector similarity score defining a similarity between each of the vectors by the key dialogues engine;
storing the vector similarity score of the each of the associated transcript data elements in a similarity matrix by the key dialogues engine; and
converting the similarity matrix into a graphical representation by the key dialogues engine for computation of a rank of the each of the associated transcript data elements.