Information processing device and information processing method

An information processing method, comprising:

• in an information processing device:
• learning a learning model;
• receiving text data;
• extracting, from the text data, line sentence data and one of stage direction data or descriptive part data;
• decomposing the line sentence data into morphological sequences;
• extracting a feature amount from the morphological sequences;
• detecting a first expression based on;
• the learning model,
• the extracted feature amount, and
• character information including information of a plurality of characters, wherein
• the first expression is in the line sentence data, and
• the first expression indicates a respective character likeness of each of the plurality of characters:
• generating a second expression based on the first expression and the character information, wherein
• the second expression is associated with the respective character likeness, and
• the second expression is different from the first expression:
• presenting the second expression;
• and
• relearning the learning model based on a feedback from a user to the second expression.

An information processing device, comprising:

• a central processing unit (CPU) configured to:
• receive text data;
• extract a feature amount from the text data;
• detect a first expression based on the extracted feature amount, and character information that includes information of a character using a learning model learned in advance, wherein
• the first expression is in the text data, and
• the first expression indicates a character likeness of the character;
• determine, based on the character information of each of a plurality of characters, a comparison result between a respective character likeness of each of the plurality of characters for the first expression;
• generate a second expression based on the first expression, the character information, and the comparison result, wherein
• the second expression is associated with the respective character likeness of each of the plurality of characters, and
• the second expression is different from the first expression;
• present the second expression;
• present, for the first expression, a list of a plurality of values that indicates the respective character likeness of the each of the plurality of characters;
• and
• relearn the learning model based on a feedback from a user to the second expression.