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.- Anthology ID:
- 2021.icon-main.10
- Volume:
- Proceedings of the 18th International Conference on Natural Language Processing (ICON)
- Month:
- December
- Year:
- 2021
- Address:
- National Institute of Technology Silchar, Silchar, India
- Editors:
- Sivaji Bandyopadhyay, Sobha Lalitha Devi, Pushpak Bhattacharyya
- Venue:
- ICON
- SIG:
- Publisher:
- NLP Association of India (NLPAI)
- Note:
- Pages:
- 75–79
- Language:
- URL:
- https://aclanthology.org/2021.icon-main.10
- DOI:
- Cite (ACL):
- Yeoun Yi and Hyopil Shin. 2021. Generating Slogans with Linguistic Features using Sequence-to-Sequence Transformer. In Proceedings of the 18th International Conference on Natural Language Processing (ICON), pages 75–79, National Institute of Technology Silchar, Silchar, India. NLP Association of India (NLPAI).
- Cite (Informal):
- Generating Slogans with Linguistic Features using Sequence-to-Sequence Transformer (Yi & Shin, ICON 2021)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/2021.icon-main.10.pdf