@inproceedings{yi-shin-2021-generating,
    title = "Generating Slogans with Linguistic Features using Sequence-to-Sequence Transformer",
    author = "Yi, Yeoun  and
      Shin, Hyopil",
    editor = "Bandyopadhyay, Sivaji  and
      Devi, Sobha Lalitha  and
      Bhattacharyya, Pushpak",
    booktitle = "Proceedings of the 18th International Conference on Natural Language Processing (ICON)",
    month = dec,
    year = "2021",
    address = "National Institute of Technology Silchar, Silchar, India",
    publisher = "NLP Association of India (NLPAI)",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.icon-main.10/",
    pages = "75--79",
    abstract = "Previous work generating slogans depended on templates or summaries of company descriptions, making it difficult to generate slogans with linguistic features. We present LexPOS, a sequence-to-sequence transformer model that generates slogans given phonetic and structural information. Our model searches for phonetically similar words given user keywords. Both the sound-alike words and user keywords become lexical constraints for generation. For structural repetition, we use POS constraints. Users can specify any repeated phrase structure by POS tags. Our model-generated slogans are more relevant to the original slogans than those of baseline models. They also show phonetic and structural repetition during inference, representative features of memorable slogans."
}