Visualizing Natural Language Descriptions: A Survey <s> Scene Maker <s> In this paper we present a linguistic resource for the lexical representation of affective knowledge. This resource (named WORDNETAFFECT) was developed starting from WORDNET, through a selection and tagging of a subset of synsets representing the affective <s> BIB001 </s> Visualizing Natural Language Descriptions: A Survey <s> Scene Maker <s> Our proposed software system, SceneMaker, aims to facilitate the production of plays, films or animations by automatically interpreting natural language film scripts and generating multimodal, animated scenes from them. During the generation of the story content, SceneMaker will give particular attention to emotional aspects and their reflection in fluency and manner of actions, body posture, facial expressions, speech, scene composition, timing, lighting, music and camera work. Related literature and software on Natural Language Processing, in particular textual affect sensing, affective embodied agents, visualisation of 3D scenes and digital cinematography are reviewed. In relation to other work, SceneMaker will present a genre-specific text-to-animation methodology which combines all relevant expressive modalities. In conclusion, SceneMaker will enhance the communication of creative ideas providing quick pre-visualisations of scenes. <s> BIB002 </s> Visualizing Natural Language Descriptions: A Survey <s> Scene Maker <s> Producing plays, films or animations is a complex and expensive process involving various professionals and media. Our proposed software system, SceneMaker, aims to facilitate this creative process by automatically interpreting natural language film scripts and generating multimodal, animated scenes from them. During the generation of the story content, SceneMaker gives particular attention to emotional aspects and their reflection in fluency and manner of actions, body posture, facial expressions, speech, scene composition, timing, lighting, music and camera work. Related literature and software on Natural Language Processing, in particular textual affect sensing, affective embodied agents, visualisation of 3D scenes and digital cinematography are reviewed. In relation to other work, SceneMaker follows a genre-specific text-to-animation methodology which combines all relevant expressive modalities and is made accessible via web-based and mobile platforms. In conclusion, SceneMaker will enhance the communication of creative ideas providing quick pre-visualisations of scenes. <s> BIB003
SceneMaker BIB002 BIB003 is a collaborative and multi-modal system designed for pre-visualizing the scenes of given scripts to facilitate the movie production process. This system is a successor of the CONFUCIS system and exploits its underlying language processing and multi-modal animation generation tools. SceneMaker expands CONFUCIS by adding common-sense knowledge for genre specification, emotional expressions, and capturing emotions from the scripts. Users can edit the generated animation online via mobile devices. SceneMaker consists of two layers, including a user interface that can run on a PC or a mobile device and a scene production layer running on a server. The user interface receives a screenplay from the user and provides her with a 3D animation of the script and a scene editor to edit the generated animation. The scene production layer contains three components operating in a serial manner, including an understanding module, a reasoning module, and a visualization module. The understanding module performs text analysis using the CONFUCIS platform. The reasoning module uses WordNetAffect BIB001 -an extension to WordNet and ConceptNet to interpret the context, manage emotions, and plan the actions. The visualization module fetches the corresponding 3D models and music from the database, generates speech, and sets the camera and lighting configuration. Despite adding interactions and alleviating input restrictions, SceneMaker inherits the flaws of CONFUCIS in terms of action definition. It is noteworthy that we could not find any snapshots of the resulting animation in the published articles.