{
    "paper_id": "2019",
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        "date_generated": "2023-01-19T12:37:25.034144Z"
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        "abstract": [],
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            {
                "text": "Welcome to the 4th Workshop on Computational Creativity in Language Generation, a workshop held in conjunction with INLG 2019, the International Conference on Natural Language Generation, in Tokyo, Japan.",
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                "section": "Introduction",
                "sec_num": null
            },
            {
                "text": "Discussions at CC-NLG will cover the distinct approaches of CC and NLG brought about by their respective focuses; research in computational creativity has tended to deal less with technical shifts, directed instead at cognition, aesthetics, and novelty; whilst NLG research has tended to focus on the technical and theoretical challenges of topics like readability. However, in recent years this distinction has become far less defined. NLG research deals actively with concepts of style, variation, poetics, and narrative, whilst creative researchers are developing robust implementations. This change can be seen in dialogue systems, where the usability of an interface relies on it handling out-of-domain or spontaneous user input. Creative methodologies are garnering fundamental and applicable returns.",
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                "section": "Introduction",
                "sec_num": null
            },
            {
                "text": "-The Organizers ",
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                "section": "Introduction",
                "sec_num": null
            }
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            "TABREF0": {
                "content": "<table><tr><td>Toward Text Embellishment using Attention Based Encoder-Decoder Model Subhajit Naskar,</td></tr></table>",
                "text": "Automated Quest Generation in Text-Adventure Games Prithviraj Ammanabrolu, William Broniec, Alex Mueller, Jeremy Paul and Mark Riedl. . . . . . . . . . . . . . . 1 Efficient text generation of user-defined topic using generative adversarial networks Chenhan Yuan, Yi-Chin Huang and Cheng-Hung Tsai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Emotional Neural Language Generation Grounded in Situational Contexts Sashank Santhanam and Samira Shaikh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Soumya Saha and Sreeparna Mukherjee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Noun Generation for Nominalization in Academic Writing Dariush Saberi and John Lee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Advertising Plot Generation System Based on Comprehensive Narrative Analysis of Advertisement Videos Juumpei Ono, Atsushi Sasaki and Takashi Ogata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 vii",
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