METHOD OF ANIMATING SMS-MESSAGES

• US 20140225899A1
• Filed: 12/08/2011
• Published: 08/14/2014
• Est. Priority Date: 12/08/2011
• Status: Active Grant

• Current Assignee: Bazelevs Entertainment Limited
• Original Assignee: Bazelevs Innovations Ltd.
• Inventors: Bekmambetov, Timur N., Kuzmin, Sergei V., Novosyolov, Anton A.
• Granted Patent: US 9,824,479 B2
• Time in Patent Office: Days
• US Class Current: 345/473
• CPC Class Codes: G06F 40/186 Templates
• CPC Class Codes: G06T 13/80 2D [Two Dimensional] animation, e.g. using sprites
• CPC Class Codes: G06T 2213/12 Rule based animation
• CPC Class Codes: H04L 51/10 Multimedia information
• CPC Class Codes: H04L 51/58 Message adaptation for wireless communication
• CPC Class Codes: H04W 4/12 Messaging; Mailboxes; Announcements

Abstract

The present invention relates to rendering texts in a natural language, namely to manipulating a text in a natural language to generate an image or animation corresponding to this text. The technical effect achievable from the use of the claimed invention consists in expanding the range of technical facilities as related to rendering a text written in a natural language (obtaining animations using the text). The invention is unique mainly in that a sequence of animations is selected, semantically corresponding to a given text. Given a set of animations and a text, the invention makes it possible to compare the sequence of these animations to this text. It is unique in that text templates are used and a optimum sequence of these templates is determined. The idea of the templated text rendering consists in that the text is manipulated to generate an image or animation with the aid of searching correspondences to a limited number of predefined templates. An animation according to certain style is selected in compliance with each template. Animations are sequentially combined into a single sequence of video images.

Claims

1. A method for selecting animations corresponding to a text in a natural language, said method comprising the steps of:

receiving a text of request in a natural language;

dividing said text into sentences;

dividing said sentences into words;

reducing each word to a normalized form;

selecting a sequence of templates for the normalized text;

combining the sequences of templates for each sentence in a certain order into a single common sequence of templates;

selecting an animation for each template;

combining the selected animation files into a resulting clip.

2. The method of claim 1, characterized in that words, phrases and symbols are formally replaced in the predefined words, phrases or symbols equivalent thereto.

3. The method of claim 1, characterized in that misprints are corrected in the words.

4. The method of claim 1, characterized in that neutral background animations for each template are selected if necessary.

5. The method of claim 1, characterized in that it is determined whether any sequences of templates corresponding to the normalized text are available in the cache, wherein

if a sequence of templates is available in the cache, the sequence of templates is selected from the cache.

6. The method of claim 1, characterized in that it is determined whether an animation style is set for the incoming text, wherein

if the style is set, animations corresponding to the style are selected provided that for the selected style, an animation of each template from the sequence is available in this style;

and

if no style is set, the style is randomly selected for which all animations are available for the selected templates;

if there is a number of such styles, any style is randomly selected;

if no styles are available, a selection of animations in various styles is used.

7. The method of claim 1, characterized in that the original text of request, the selected sequence of templates are saved in the database;

and

statistics for templates, words, animations, the list of unknown words and statistics for unknown words is updated.

16. A method of animation of SMS messages, said method comprising the steps of:

receiving a SMS message from a sender;

analyzing the received SMS message by defining the message text;

sending a request containing the text to an animation service;

selecting animations using the method of claim 1;

combining the selected animations and sending to a service processing service;

forming an MMS containing the received animation and sending to a recipient.

17. The method of claim 16, characterized in that the recipient'"'"'s subscriber number and the message text are included in the SMS message.

18. The method of claim 16, characterized in that the sender and the recipient are identified in the received SMS message.

19. The method of claim 16, characterized in that a SMS message is sent to the sender saying that the animation has been sent or failed.

20. A method of animation of SMS messages, said method comprising the steps of:

receiving a SMS message from a subscriber;

analyzing the received SMS message by defining the message text;

sending a request containing the text to an animation service;

selecting and image or animations using the method of claim 1;

sending the selected image or animations to a service processing service;

forming an MMS containing the received image or animation and sending to a subscriber.

21. The method of claim 20, characterized in that the subscriber is identified in the received SMS message.

8. A method for searching an optimum sequence of templates for subsequently selecting animations corresponding to the sequence of templates, comprising the steps of:

a) selecting from the list, all templates having all template words included in a sentence, wherein if a particular animation style is set, selecting templates from the list of templates having animations in the selected style rather than from the list of all templates;

b) deriving from the list of templates obtained in the previous step, the information regarding the hierarchy of templates, wherein the template hierarchy level determines the template rank;

c) if templates belonging to the same hierarchy but having different levels are included in a single set of templates obtained in step a), deleting from this set the templates with a minimum rank (a higher level);

d) selecting from the list of templates obtained in step c), an optimum set of templates for which a target function will have the most optimum value,

wherein the target function is given by;

9. The method of claim 8, characterized in that an optimum value of the target function is searched either by means of an exhaustive search of the sequence of templates (successively going through all combinations of unique templates) or by means of multicriteria optimization.

10. The method of claim 8, characterized in that it is determined whether any sequences corresponding to the normalized test are available in the cache, wherein,

wherein if a sequence of templates is available in the cache, the sequence of templates is selected from the cache.

11. The method of claim 8, characterized in that it is determined whether an animation style is set for the incoming text, wherein

if the style is set, animations corresponding to the style are selected provided that for the selected style, an animation of each template from the sequence is available in this style;

and

if no style is set, the style is randomly selected for which all animations are available for the selected templates;

if there is a number of such styles, any style is randomly selected;

if no styles are available, a selection of animations in various styles is used.

12. The method of claim 8, characterized in that the original text of request, the selected sequence of templates are saved in the database;

and

statistics for templates, words, animations, the list of unknown words and statistics for unknown words is updated.

13. The method of searching an optimum sequence of templates for subsequently selecting animations corresponding to the sequence of templates, said method comprising the steps of:

using the Levenshtein edit-distance algorithm, finding all templates all words of which are found in the phrase being sought;

sorting the found templates by the number of words in ascending order;

sequentially determining for each template from this formed set of templates, whether the template is part of any other template from the set, wherein if the template is part of any other template from the set, deleting the same;

in the resulting set of templates, defining the templates non-crossing each other and crossing each other;

adding the non-crossing templates to the resulting set;

calculating for each template an average value of the template word positions in the text; and

sorting the templates by that average value to obtain an optimum sequence of templates.

14. The method of claim 13, characterized in that the rate of crossing (number of word crosses) of the words from the set of non-crossing templates and the number of new words not included in this set, covering the phrase is determined in the crossing templates.

15. The method of claim 13, characterized in that if no non-crossing templates exist, an optimum set of templates is formed from the crossing templates, considering the following criteria:

maximum aggregate rank, maximum coverage, minimum crosses;

wherein

the set of templates is formed by carrying out the following steps of;

a) selecting a first template with a maximum weight, said template weight being the number of words in the template;

b) selecting templates minimally crossing the first template and non-crossing each other;

c) selecting from the remaining templates those templates that contain >

=50% of new words;

wherein

d) if in step a) a few templates with a maximum weight were available, selecting as the resulting set of templates the set having a maximum difference between the aggregate rank of templates and the number of word crosses.