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SentEmojiBot: Empathising Conversations Generation with Emojis

arXiv 2105.12399 ↗First posted 26 May 2021cs.CLcited by 0

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Abstract (arXiv)

The increasing use of dialogue agents makes it extremely desirable for them to understand and acknowledge the implied emotions to respond like humans with empathy. Chatbots using traditional techniques analyze emotions based on the context and meaning of the text and lack the understanding of emotions expressed through face. Emojis representing facial expressions present a promising way to express emotions. However, none of the AI systems utilizes emojis for empathetic conversation generation. We propose, SentEmojiBot, based on the SentEmoji dataset, to generate empathetic conversations with a combination of emojis and text. Evaluation metrics show that the BERT-based model outperforms the vanilla transformer model. A user study indicates that the dialogues generated by our model were understandable and adding emojis improved empathetic traits in conversations by 9.8%

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 33 references that are in the map. First posted on arXiv 26 May 2021.

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14 of 33 references.

References · 14

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  2. 2014Convolutional Neural Networks for Sentence Classificationcited by 1,124
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  9. 2017Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasmcited by 117
  10. 2017MojiTalk: Generating Emotional Responses at Scalecited by 64
  11. 2018Learning Semantic Textual Similarity from Conversationscited by 41
  12. 2015Sentiment of Emojiscited by 31
2 more
  1. 2016emoji2vec: Learning Emoji Representations from their Descriptioncited by 28
  2. 2016Lifted Rule Injection for Relation Embeddingscited by 22

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