Patent ID: 11935518
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. A joint works production server using collective intelligence, the joint works production server comprising:
a subject receiving unit configured to receive a subject of joint works from participants of the joint works production;
a subject classifying unit configured to classify, when the subject of the joint works is adopted, the adopted subject of the joint works by subjects;
an episode receiving unit configured to receive a candidate episode from each of the participants who selected the same subject among the classified subjects from the participants;
a voice data generating unit configured to convert each of the received candidate episodes into voice data and to transmit each candidate episode converted into the voice data to evaluators;
an impression index generating unit configured to receive brainwave information indicating a change in brainwaves of the evaluators according to the candidate episode converted into voice from the evaluators and calculate impression indexes by applying a higher weight to a time for brainwave detection of a specific frequency than an amount of change in the brainwaves;
an episode selecting unit configured to select episodes among the candidate episodes in order of the impression indexes; and
a manuscript creating unit configured to create a manuscript by arranging a sequence of selected episodes using a second neural network model trained to determine a correlation between the selected episodes based on ontology;
wherein the voice data generating unit generates the voice data by adjusting at least one of an intensity, a tempo, and an intensity change pattern of a voice signal according to each section of the candidate episode based on an emotional state analyzed by a first neural network model trained to classify a pattern of words as the section in which people are impressed, and
wherein the second neural network model organizes an order of episodes with the highest emotional index by predicting an impression index of the created manuscript through the first neural network model.