Development of AniDB and AniXML Schema for Semi-Autonomous Animation Contents Generation using Korean Fairy Tale Text

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1 Development of AniDB and AniXML Schema for Semi-Autonomous Animation Contents Generation using Korean Fairy Tale Text Young-One Cho, Byung-Chul So and + Jin-Woo Jung, Department of Computer Engineering, Dongguk University, Korea one2003@hanmail.net, sbc10620@naver.com, jwjung@dongguk.edu Abstract In this paper, we propose a model of AniDB and AniXML schema to generate animation using Korean fairy tale text. AniDB is divided into two classes, the dictionary part and the animation element part. The dictionary part is used for semantic analysis and emotion analysis. The result of two analyses, AniXML is an interim language for the generation of animation. The elements of AniXML are connected to the animation element part of AniDB and combine the images and music. The combination will be the animation of fairy tale. I. INTRODUCTION Contents are defined as a creation that is provided by media. Contents may have variable shapes, consisting of music, movie, cartoon, game and so on [1]. There are some contents used for the kid, and they are called as kid contents. Currently, according to advance of internet, an e-book is in the spotlight of kid contents area. The e-book is a special formatted file, and can be shown in the mobile device or computer. Specially, the kid e-book is made as animation, including narration and background music that describe a fairy tale synopsis. In this paper, we will propose the design of the AniDB database, AniXML schema and interpretation method of a fairy tale sentence structure used in The Semi-Automated Fairy Tale Animation Generator, to create animation in kid content. The Semi-Automated Fairy Tale Animation Generator extracts character, action, background, and emotion information from korea fairy tale text. And this information is used to create a fairy tale animation semi-automatically. For this task, we defined AniDB database to save extracted information from a fairy tale and AniXML to interact between the animation generator and AniDB. And we will discuss how these two factors are used in the Semi-Automated Fairy Tale Animation Generator. II. RELATED WORK The AniDB database has character, action, background, and emotion information to express a fairy tale by animation. A fairy tale story is analyzed and compared with AniDB for choosing the valid phrases that can be animated. And chosen phrases are recreated to AniXMLs. The animation generator uses information of AniXML to choose a predefined character and create animation semi-automatically. Hence, they can create media content based on a fairy tale for kids although user is an amateur. In the past, we needed the entire images for creation of the animation. But the digital technology operated remarkable changes about this general practice. Now all images are stored on the database system as it is, and then new images are created easily by modifying and mixing stored data if it is necessary. In other words, the digital animation can be created like printed books. According to reuse of stored images in the database, making the digital animation becomes efficiency and economical[2]. To interpret a fairy tale sentences and create animation by using the database, it requires emotion analysis and semantic analysis before anything else. A result of semantic analysis represents fairy tale phrases about parsing tree, and we can extract information about a fairy tale from parsing tree by using loops to traverse tree. And by using emotion analysis, we can extract positive or negative emotion of characters from the fairy tale story. There are variable models to represent emotion information, Valence-Arousal space, OCC model and Flame model. First, Valence-Arousal space can be used to represent degree of emotion and positive or negative emotion. This model is known as an efficient tool to represent human emotion in 2D-space [3]. OCC(Ontology, Clore and Colins) model does not represent all of human emotion. But this model classifies each emotion to emotional categories. And emotions in + : Corresponding author

2 same emotional categories have similar cause which results in this emotion [4]. FLAME(Fuzzy Logic Adaptive Model of Emotions) model uses fuzzy logic to represent relation among events, objects, and expectations. This model can express human emotion changes flexibly[5]. Also XML can represent human emotion. EmotionML (Emotion Markup Language) can express human emotion by using three methods that are based on compute communication. These three methods are as follows, Manual annotation of data, automatic recognition of emotion-related states from user behavior and generation of emotion-related system behavior [6]. III. OVERALL SYSTEM STRUCTURE The Semi-Automated Fairy Tale Animation Generator we study is like Figure 1. First, it analyzes the morpheme and syntax of fairy tale text. Then, it carries out semantic and emotional analysis about syntax tree through connection with Database AniDB. AniXML results from the step of semantic and emotional analysis. AniXML is an interim language for the generation of animation directly. Animation Generator interprets AniXML and combines character images and music files existed in dictionary part of AniDB. The quality of animation depends upon the result of AniXML. Therefore, AniDB structure and AniXML definition will be the main factors in our system. 1. Morphological and Syntax Analyzer Morphological analysis is first step in natural language analysis. Morphological analysis recognizes each morpheme in a word, and restores the original form if change happened in a word, for example, conjugates irregularly, abbreviation, and so on. Morphological analysis takes pre-processing documents as input and performs POS (Part-of-speech) tagging on each words to refer in syntactic analysis step. Morphological analysis has difference approach according to characteristic of each language. In Korean, ratio of token and morpheme is 1:N, such language is called by inflected language. And in English, ratio of token and morpheme is 1:1; such language is called by isolated language. As above, Korean is inflected language and specially has high error rate about spacing of the words. Hence, Korean is not easy to analyze morpheme mechanically. The result data of morphological analysis is used in syntactic analysis to make parsing tree. Parsing tree represents syntactic analysis of correct sentence. And meaning is given to sentence by using parsing tree. We applied Morpheme and Syntax analyzer about fairy tale using an opened practical application. We should have considered that the fairy tale doesn t follow the normalized structure consisting of the subject, the object, the predicate of sentence. Also, it is similar with a conversational style. We regarded the characteristic of the fairy tale and supposed the matters like this list.. a. use the subject of previous paragraph if the subject doesn t exist in current paragraph b. ignore sentences written in conversational style c. deactivate the animation of sentence included the time words like tomorrow, later, and so on. We analyzed the morphemes and syntaxes about the fairy tale texts and outputted syntax tree as a result of them. And we extracted a noun, the verb, and adjective words from syntax tree. Then, we implemented the semantic and emotional analysis for those words and constructed the dictionary of AniDB. 2. Semantic and Emotional Analyzer Figure 1. Structure of the Semi-Automated Fairy Tale Animation Generator In this study, we defined four elements consisted of character, action, background, and emotion. These are the necessary components for making animation based on the story of fairy tale. A movement of the main characters is made by a combination of character and action elements. Our system expresses the background

3 elements in background images and the emotion elements are to be connected to music files. Therefore the noun word extracted from syntax tree should be defined if it is the subject, object or background in a sense. Also, the verb word is asked whether It means action or not. And, our system distinguishes the positive emotion from the negative emotion in the adjective word. We show the classification of items for semantic and emotional analysis in table 1. It is connected to database structure directly. Except for that we didn t consider about the words we can t make the animation like time words. Table 1. Classification of words for semantic analysis and emotional analysis words Semantic analysis Emotional analysis Noun subject - background - object - Verb action - Adjective - Positive - negative IV. ANIDB AND ANIXML SCHEMA DESIGN 1. AniDB schema definition Our database system, AniDB is divided into two classes, the dictionary part and the animation element part. We already showed the dictionary part of AniDB in Table 2. The dictionary part of AniDB consists of a character table, a background table, action table, and emotion table. The character table has the subject and object elements extracted from the noun words. The background table has the words with background meanings in the noun words. The verb words with movement meanings are stored in action table and the positive or negative words are saved in emotion table. The tables of the dictionary part are used in step of AniXML generation. We don t use all of fairy tale sentences. We should find out the animate words from syntax tree through semantic and emotional analysis. Second, the animation part of AniDB has a character image table, background image table, and music table. Animation generator refers to AniDB with AniXML and outputs an animation. It connects the words of character table to the images of character image table, the words of background table to the images of background image table, and the elements of emotion table to the files of music table. The movement of characters, background images, and music files are chosen randomly, continuously. We will not mention about these in detail because the algorithm for animation creation is handled from different point of view. a. Background table and character table The character table and background table is created through semantic analysis. The identity of background table is constrained in items like mountain, river, sea, field, backyard, home, and so on. For example, sea will be chosen as background if we find out the noun words like whale, shark in paragraph. The character table consists of character identity and category identity. The character identity of it has the subjects or objects for creation of animation and the category identity of it has general and specialize values. The general character is no specialized subjects or objects. For example, we can choose one flower image among several kinds of flowers if character is flower and category is general. The special character means the one having the name of their own like well-known Pororo over Korea. Figure 2 shows the structure of character table and background table. The Background table connects Background image table to background elements in Noun table. The Character table contains character elements categorized by Category table. The Character character image table connects the elements of Character table to Character image table. Figure 2. Definition of character and background table

4 b. Emotion table We analyzed the adjective words extracted from syntax tree and made the emotion table. The identity of emotion table has two values, positive and negative. Also, the music table has two kinds of music files. The music will be chosen and played among the files in positive identity of the music table if the positive emotion is recognized. Figure 3 shows the structure of emotion table. We defined the movement identity in each of verb identities. The movement identity of action table has the values like move, rotate, show, disappear, enlarge, reduction, and so on. For example, we combine the subject and object in same sentence if we extract the animate verb included in third sentence pattern. The subject will take a motion defined in the movement identity. Figure 4 shows the structure definition about action table. 2. AniXML schema definition The result of semantic analysis and emotion analysis on each paragraph in a fairy tale is represented by using XML. A paragraph has more than one animation, background and background music. In this paper, we named this XML AniXML. Figure 5 represents DTD definition about AniXML. c. Action table Figure 3. Definition of emotion table Korean sentence is classified by three kinds of sentence pattern [8]. The first sentence pattern composed of Subject and predicate. The second sentence pattern composed of Subject and object and predicate. The third sentence pattern has the composition of 4 elements. The classification of the sentence pattern depends on the characteristic of verbs. We applied the rule of sentence pattern classification as we create the action table. What the verbs included in is specified on the action table. In case of verb included in first sentence pattern, the verb needs the only subject. It needs the subject and object in case of second sentence pattern. The verb in third sentence patter needs three elements. We redefined the objective complements added as interaction objects (with/to). The interaction objects would be friends, family, and so on of the main character. Figure 4. Definition of action table <?xml version="1.0" encoding="utf-8"?>  <!ELEMENT fairytale (paragraph)+ > <!ELEMENT paragraph (emotion,background,animation)> <!ELEMENT emotion (#PCDATA)> <!ELEMENT background (#PCDATA)> <!ELEMENT animation (character)+> <!ELEMENT character (action)?> <!ELEMENT action (object, withorto)> <!ELEMENT object EMPTY> <!ELEMENT withorto EMPTY> <!ATTLIST character name CDATA #REQUIRED> <!ATTLIST action verb CDATA #REQUIRED> <!ATTLIST object name CDATA #REQUIRED> <!ATTLIST withorto name CDATA #REQUIRED> Figure 5. DTD definition of AniXML The root element of AniXML is the fairytale element. And the fairytale element has the paragraph element. The paragraph element has background, emotion, and animation information about each paragraph in a fairy tale. The number of paragraph element in root element is same to the number of paragraph in a fairy tale. The animation generator reads sequentially information in the paragraph element and creates animation for kids. The emotion element in the paragraph element has emotion information about paragraph. The animation generator uses this information to choose emotion-based

factor, for example, background music. And the background element represents a background of animation. The animation element has important animation information about the paragraph.

5 factor, for example, background music. And the background element represents a background of animation. The animation element has important animation information about the paragraph. The animation element has the character element by child. The character element has practical information to implement each animation. One paragraph is expressed by several animations. Hence, in the character element, the animation element can be used repeatedly. The character element has the action element by child, and the action element defines motion of characters. Also the action element has the object element and the withorto element. The object element describes subject in an animation and the withorto element describes character that interacts with subject. Each character has a basic action motion. If an action information of a character doesn t recognize in a paragraph, this basic action is used. And also if background and emotion information doesn t recognize in a paragraph, extract these information from a previous paragraph. V. MODEL VALIDATION In the Semi-Automated Fairy Tale Animation Generator, It implements the morpheme analysis and syntax analysis about fairy tale text at first step. The result of first step is the syntax tree and it will be the input of next step. Our system carries out Semantic and emotional analysis about syntax tree. It needs the connection with AniDB in this step. The result of semantic and emotional analyzer is an interim language, AniXML. Finally, AniXML is to be the input of animation generator. Animation generator interprets AniXML and combines the images and music files in animation elements part of AniDB. This is the animation of fairy tale. INPUT:A rabbit threw a ball to a bear F threw V:thr P:ew E:ow O a ball N:ball J:a B to a bear N:bear J:to a S A rabbit N:rabbit J:A Figure 6. Result of morpheme and syntax analysis (a) Result of pasing program (b) English translation of result (a) by our hands Figure 6. is the result of morpheme analysis and syntax analysis about the input sentence, 토끼가곰에게공을던졌다 (A bunny throws a ball to a bear). F is predicate, O is object, B is an objective complement, and S means a subject. And the meaning of V is a verb, P is prefinal ending, E is final ending, N is a noun, and J means a particle. The noun words, like 곰 (bear), 토끼 (bunny), 공 (ball), are already existed in dictionary part of AniDB. So it will be added to AniXML. The verb word, 던지다 (throw), is in action table and inserted to AniXML, too. The word related to background and emotion is not existed. In case of this, AniXML is inherited the background and emotion information of previous paragraph. Figure 7 shows AniXML as the result of implement of this practice sentence. We supposed that the background of previous paragraph is 산 (mountain) and the emotion is 신난 (exiting). <?xml version="1.0" encoding="ks_c_ "?> <!DOCTYPE fairytale SYSTEM "fairytale-dtd.dtd"> <fairytale> <paragraph> <emotion> 신나다 </emotion>  <background> 산 </background>  <animation> <character name=" 토끼 ">  <action verb=" 던지다 ">  <object name=" 공 "/>  <withorto name=" 곰 "/>  </action> </character> </animation> </paragraph> </fairytale> Figure 7. Example of AniXML structure

6 Figure 7 represents AniXML by created from a paragraph in a fairy tale. And the animation generator interacts with AniXML and AniDB to create animation. The emotion element in figure 3 has 신난 (exciting), this adjective close to positive. Therefore, a background music that involves exciting mood will be chosen. And background of animation is used a mountain image because the background element has 산 (mountain). And in the paragraph element, the subject of animation is 토끼 (bunny), the action is 던지다 (throw), the object is 공 (ball) and the interaction object is 곰 (bear). The 던지다 action performs pre-defined action in AniDB database. According to 던지다 (throw) action, the animation is composed the rotation of arms of 토끼 (bunny), moving of 공 (ball) and rotation of arms of interaction object 곰 (bear). The animation generator interprets these actions and brings image and music file to create animation. AniXML is composed of several paragraphs. Therefore a fairy tale animation is created by combination of paragraphs in AniXML. VI. CONCLUSION We defined the model of AniDB and AniXML schema for The Semi-Autonomous Fairy-Tale Animation Generator of Korean fairy tale text. AniDB is divided into two classes, the dictionary part and the animation element part. We defined four elements consisted of character, action, background, and emotion for the dictionary part of AniDB. The character and background words are extracted from noun words through semantic analysis. The action information is extracted from verb words, too. We can find the emotion information from adjective words through emotional analysis. Consequently, the dictionary part of AniDB consists of four tables. The animation element part of AniDB has images and music files for creation of animation. Also, We defined an interim language, AniXML for the generation of animation directly. Animation Generator interprets AniXML and combines character images and music files existed in animation element part of AniDB. The combinations will be the animation of fairy tale. Therefore, the quality of animation depends upon the results of AniXML. Korea(NRF) funded by the Ministry of Education, Science and Technology( ) REFERENCES [1] On-line Wikipedia, encyclopedia, search keyword : contents(media), [2] Dong-Eun Lee, A Comparative Study for Digital Animation Production using Database, Journal of Korea Multimedia Society Vol 11. No. 1, January, pp , 2008 [3] Picard. R, Affective computing, Media Laboratory Perceptual Computing TR 321, MIT Media Laboratory, 1995 [4] Prendinger, H. and Ishizuka, M., Simulating affective communication with animated agents, Proc. Of the INTERACT 01, pp , 2001 [5] Magy S. E., Thomas R. I., John Y., Donald H. H. and Frederic I. P., Emotionally expressive agents, Proc. Of Computer Animation 99, pp , 1999 [6] Marc Schröder, Emotion Markup Language (EmotionML) 1.0 W3C Working Draft 7 April 2011, W3C, 2011 [7] Minkyu Kang, Seungshik Kang, Error Correction Method for Korean Compound Noun Decomposition, Korea Computer Congress, Vol.37, No.1, 2010 [8] Hyesook Kim, About the basic sentence pattern of Korean, The society of Korean Language and Literature, Vol.122, pp.14-47, 1998 ACKNOWLEDGEMENT This research was supported by Basic Science Research Program through the National Research Foundation of

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