Claims:WE CLAIM:
1. A computer implemented story generation system (100), said system (100) comprising:
• a repository (102) configured to store a lookup table having a list of themes, a pre-determined template associated with each of said themes, and a pre-determined set of questions corresponding to each of said templates;
• a theme selection module (104) configured to receive a first input indicative of a user’s desire to generate a story and a second input indicative of a selection of said theme of said story;
• a template extractor module (106) configured to cooperate with said theme selection module (104) to receive said second input, said template extractor module (106) further configured to cooperate with said repository (102) to crawl through said lookup table to extract said template associated with said selected theme based on said received second input; and
• a story generator module (108) configured to cooperate with said repository (102) to populate said pre-determined set of questions corresponding to selected template, and further configured to receive responses to said populated questions, said story generator module configured to perform discourse analysis on said received responses, and further configured to cooperate with said template extractor module (106) to generate a story by populating said analysed responses in a sequential manner into said extracted template,
wherein said theme selection module (104), said template extractor module (106) and said story generator module (108) are implemented using one or more processor(s).
2. The system (100) as claimed in claim 1, wherein said story generator module (108) includes:
• a first populator (110) configured to populate said pre-determined set of questions;
• a parser (112) configured to cooperate with said first populator (110) to receive responses to said populated questions, and further configured to parse said responses to generate at least one token;
• a syntactic analyser (114) configured to cooperate with said parser (112) to syntactically analyse said tokens;
• a semantic analyser (116) configured to cooperate with said syntactic analyser (114) to semantically analyse said syntactically analysed tokens;
• a combiner (118) configured to cooperate with said semantic analyser (116) to combine said semantically analysed tokens in said sequential manner of analysis; and
• a second populator (120) configured to cooperate with said combiner (118) to populate said combined tokens in said extracted template to generate said story.
3. The system (100) as claimed in claim 1, wherein said inputs are received in said form of at least one of text, audio and image.
4. The system (100) as claimed in claim 1, wherein said story is generated in said form of text, audio, or image, or any combination thereof.
5. The system (100) as claimed in claim 1, wherein said story generator module (108) is configured to store said generated story in said repository (102).
6. The system (100) as claimed in claim 5, which includes a first story combiner (122) configured to receive a selection of at least two pre-stored stories from said user, and further configured to combine said selected pre-stored stories to generate a new story.
7. The system (100) as claimed in claim 5, which includes a second story combiner (124) configured to receive a selection of at least one pre-stored story from said user, and further configured to combine said responses with said selected pre-stored story to generate a customised story.
8. The system (100) as claimed in claim 1, which includes a language selector (126) configured to facilitate said user to select a language in which said story is to be generated.
9. A computer implemented method for generating a story (200), said method comprising said steps of:
• storing (202), by a repository (102), a lookup table having a list of themes, a pre-determined template associated with each of said themes, and a pre-determined set of questions corresponding to each of said templates;
• receiving (204), by a theme selection module (104), a first input indicative of a user’s desire to generate a story and a second input indicative of a selection of said theme of said story;
• crawling (206), by a template extractor module (106), through said look up table to extract said template associated with said selected theme based on said received second input
• populating (208), by a story generator module (108), said pre-determined set of questions corresponding to selected template;
• receiving (210), by said story generator module (108), responses to said populated questions;
• performing (212), by said story generator module (108), discourse analysis on said received responses; and
• generating (214), by said story generator module (108), a story by populating said analysed responses in a sequential manner into said extracted template.
, Description:FIELD
The present disclosure relates to the field of story generation, more particularly to a computer implemented story generation system.
DEFINITIONS
As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used indicate otherwise.
Discourse analysis: It is an approach to the analysis of written, vocal, or sign language use, or any significant semiotic event. It’s the analysis of language 'beyond the sentence'.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
Nowadays, parents are too busy to spend time with the kids. They do not have time nor the creativity to think or create new stories to tell to the kids. There are websites that help parents to generate stories for their kids, but the website often asks too many questions. Moreover, the stories generated are somehow not relevant to the kids. The kids wish to see their favorite character in the story enacting in the story line created by them. Further, the kids and the parents face language barrier as there are hardly one or two languages present for a selection to be made for the story narration. To add to this, there is often a limit to the story length. Also, the story generated is rarely in any other form apart from text, which becomes monotonous for the kid. Most importantly, there is no selection of genre to capture the attention of the kid. And lastly, for the kid to learn moral values and ethics, the parents are unable to create stories which can reflect these virtues, which are really important at this time.
There is, therefore, felt a need of a computer implemented story generation system and a method thereof which solves the problems as described herein above.
OBJECTS
The background information herein below relates to the present disclosure but is not necessarily prior art.
An object of the present disclosure is to provide a computer implemented story generation system.
Another object of the present disclosure is to provide a system that asks less questions for generating a story.
Yet another object of the present disclosure is to provide a system that can generate a story in any language.
Still another object of the present disclosure is to provide a system that has no word limit.
Yet another object of the present disclosure is to provide a system that allows kids to generate story on their own.
Still another object of the present disclosure is to provide a system that provides story in any form like text, audio, image and any combination thereof.
Yet another object of the present disclosure is to provide a system that allows parents and kids to select any genre.
Still another object of the present disclosure is to provide a system that allows to combine more than one story to generate a new story.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
The present disclosure envisages a computer implemented story generation system comprises a repository, a theme selection module, a template extractor module and a story generator module.
The repository is configured to store a lookup table having a list of themes, a pre-determined template associated with each of the themes, and a pre-determined set of questions corresponding to each of the templates.
The theme selection module is configured to receive a first input indicative of a user’s desire to generate a story and a second input indicative of a selection of the theme of the story.
In an embodiment, the inputs are received in the form of at least one of text, audio and image.
The template extractor module is configured to cooperate with the theme selection module to receive the second input. The template extractor module is further configured to cooperate with the repository to crawl through the lookup table to extract the template associated with the selected theme based on the received second input.
The story generator module is configured to cooperate with the repository to populate the pre-determined set of questions corresponding to selected template, and is further configured to receive responses to the populated questions. The story generator module is configured to perform discourse analysis on the received responses, and is further configured to cooperate with the template extractor module to generate a story by populating the analysed responses in a sequential manner into the extracted template.
In an embodiment, the story generator module includes a first populator, a parser, a syntactic analyser, a semantic analyser, a combiner, a second populator.
The first populator is configured to populate the pre-determined set of questions. The parser is configured to cooperate with the first populator to receive responses to the populated questions, and is further configured to parse the responses to generate at least one token. The syntactic analyser is configured to cooperate with the parser to syntactically analyse the tokens. The semantic analyser is configured to cooperate with the syntactic analyser to semantically analyse the syntactically analysed tokens. The combiner is configured to cooperate with the semantic analyser to combine the semantically analysed tokens in the sequential manner of analysis. The second populator is configured to cooperate with the combiner to populate the combined tokens in the extracted template to generate the story.
In another embodiment, story is generated in the form of text, audio, or image, or any combination thereof.
In another embodiment, the story generator module is configured to store the generated story in the repository.
In another embodiment, a first story combiner is configured to receive a selection of at least two pre-stored stories from the user, and is further configured to combine the selected pre-stored stories to generate a new story.
In another embodiment, a second story combiner is configured to receive a selection of at least one pre-stored story from the user, and is further configured to combine the responses with the selected pre-stored story to generate a customised story.
In another embodiment, a language selector is configured to facilitate the user to select a language in which the story is to be generated.
The theme selection module, the template extractor module and the story generator module are implemented using one or more processor(s).
The present disclosure envisages a method for generating a story.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
A computer implemented story generation system and a method thereof of the present disclosure will now be described with the help of the accompanying drawing, in which:
Figure 1 illustrates a block diagram of a computer implemented story generation system; and
Figures 2a and 2b illustrate a flow diagram of a method for generating a story.
LIST OF REFERENCE NUMERALS
100 system
102 repository
104 theme selection module
106 template extractor module
108 story generator module
110 first populator
112 parser
114 syntactic analyser
116 semantic analyser
118 combiner
120 second populator
122 first story combiner
124 second story combiner
126 language selector

DETAILED DESCRIPTION
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawing.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details, are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well-known processes, well-known apparatus structures, and well-known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a,” "an," and "the" may be intended to include the plural forms as well, unless the context clearly suggests otherwise. The terms "comprises," "comprising," “including,” and “having,” are open ended transitional phrases and therefore specify the presence of stated features, integers, steps, operations, elements, modules, units and/or components, but do not forbid the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
A computer implemented story generation system and a method thereof of the present disclosure, is described with reference to Figure 1 through Figure 2b.
Referring to Figure 1, a computer implemented story generation system (hereinafter referred to as “system (100)”) comprises a repository (102), a theme selection module (104), a template extractor module (106) and a story generator module (108).
The repository (102) is configured to store a lookup table having a list of themes, a pre-determined template associated with each of the themes, and a pre-determined set of questions corresponding to each of the templates.
The theme selection module (104) is configured to receive a first input indicative of a user’s desire to generate a story and a second input indicative of a selection of the theme of the story.
In an embodiment, the inputs are received in the form of at least one of text, audio and image.
The template extractor module (106) is configured to cooperate with the theme selection module (104) to receive the second input. The template extractor module (106) is further configured to cooperate with the repository (102) to crawl through the lookup table to extract the template associated with the selected theme based on the received second input.
The story generator module (108) is configured to cooperate with the repository (102) to populate the pre-determined set of questions corresponding to selected template, and is further configured to receive responses to the populated questions. The story generator module (108) is configured to perform discourse analysis on the received responses, and is further configured to cooperate with the template extractor module (106) to generate a story by populating the analysed responses in a sequential manner into the extracted template.
In an embodiment, the story generator module (108) includes a first populator (110), a parser (112), a syntactic analyser (114), a semantic analyser (116), a combiner (118), a second populator (120).
The first populator (110) is configured to populate the pre-determined set of questions. The parser (112) is configured to cooperate with the first populator (110) to receive responses to the populated questions, and is further configured to parse the responses to generate at least one token. The syntactic analyser (114) is configured to cooperate with the parser (112) to syntactically analyse the tokens. The semantic analyser (116) is configured to cooperate with the syntactic analyser (114) to semantically analyse the syntactically analysed tokens. The combiner (118) is configured to cooperate with the semantic analyser (116) to combine the semantically analysed tokens in the sequential manner of analysis. The second populator (120) is configured to cooperate with the combiner (118) to populate the combined tokens in the extracted template to generate the story.
In another embodiment, story is generated in the form of text, audio, or image, or any combination thereof.
In another embodiment, the story generator module (108) is configured to store the generated story in the repository (102).
In another embodiment, a first story combiner (122) is configured to receive a selection of at least two pre-stored stories from the user, and is further configured to combine the selected pre-stored stories to generate a new story.
In another embodiment, a second story combiner (124) is configured to receive a selection of at least one pre-stored story from the user, and is further configured to combine the responses with the selected pre-stored story to generate a customised story.
In another embodiment, a language selector (126) is configured to facilitate the user to select a language in which the story is to be generated.
The theme selection module (104), the template extractor module (106) and the story generator module (108) are implemented using one or more processor(s).
The processors may be general-purpose processors, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), and/or the like. The processors may be configured to retrieve data from and/or write data to a memory/repository. The memory/repository can be for example, a random access memory (RAM), a memory buffer, a hard drive, a database, an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), a read only memory (ROM), a flash memory, a hard disk, a floppy disk, cloud storage, and/or so forth.
Figures 2a and 2b illustrate a flow diagram for a method for generating a story (200). The steps include:
• Step 202: storing, by a repository (102), a lookup table having a list of themes, a pre-determined template associated with each of the themes, and a pre-determined set of questions corresponding to each of the templates;
• Step 204: receiving, by a theme selection module (104), a first input indicative of a user’s desire to generate a story and a second input indicative of a selection of the theme of the story;
• Step 206: crawling, by a template extractor module (106), through the look up table to extract the template associated with the selected theme based on the received second input
• Step 208: populating, by a story generator module (108), the pre-determined set of questions corresponding to selected template;
• Step 210: receiving, by the story generator module (108), responses to the populated questions;
• Step 212: performing, by the story generator module (108), discourse analysis on the received responses; and
• Step 214: generating, by the story generator module (108), a story by populating the analysed responses in a sequential manner into the extracted template.
The foregoing description of the embodiments has been provided for purposes of illustration and not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but, are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCEMENTS
The present disclosure described herein above has several technical advantages including, but not limited to, the realization of, a computer implemented story generation system and a method thereof, which:
• asks less questions for generating a story;
• can generate a story in any language;
• has no word limit;
• allows kids to generate story on their own;
• provides story in any form like text, audio, image and any combination thereof;
• allows parents and kids to select any genre; and
• allows to combine more than one story to generate a new story.
The foregoing disclosure has been described with reference to the accompanying embodiments which do not limit the scope and ambit of the disclosure. The description provided is purely by way of example and illustration.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
Throughout this specification the word “comprise”, or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element, or group of elements, but not the exclusion of any other element, or group of elements.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation.