| Challenge: | EmoDS can express emotions in both ways, but it is difficult to scale to large datasets. |
| Approach: | They propose an emotional dialog system that can express emotions in both ways . they use strong emotional words and neutral words to increase the intensity of emotions . |
| Outcome: | The proposed system performs better than baselines in BLEU, diversity and quality of emotional expression. |
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| Challenge: | a growing interest in neural dialogue generation systems is focusing on generating human-like responses based on past utterances . despite efforts, few consider putting restrictions on the response itself . authors present three models that concatenate the desired emotion with the source input . |
| Approach: | They propose three models that concatenate the desired emotion with the source input or push the emotion in the decoder. |
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Empathetic and Emotionally Positive Conversation Systems with an Emotion-specific Query-Response Memory (2022.findings-emnlp)
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Zhiliang Tian, Yinliang Wang, Yiping Song, Chi Zhang, Dongkyu Lee, Yingxiu Zhao, Dongsheng Li, Nevin L. Zhang
| Challenge: | Existing emotional conversation systems output responses according to either a given emotion or the user’s emotion reflected in the input queries. |
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Affect-Driven Dialog Generation (N19-1)
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| Challenge: | Existing systems for end-to-end dialog generation focus on response quality without explicit control over affective content of the responses. |
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Automatically Select Emotion for Response via Personality-affected Emotion Transition (2021.findings-acl)
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| Challenge: | Existing studies focus on rendering specified emotions in responses, yet the individual difference in emotion expression is overlooked. |
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Prompt-Guided Selective Masking Loss for Context-Aware Emotive Text-to-Speech (2025.findings-naacl)
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| Challenge: | Emotional dialogue speech synthesis (EDSS) aims to generate expressive speech by leveraging the dialogue context between interlocutors. |
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Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems (2022.acl-long)
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| Challenge: | Existing work on empathetic dialogues focused on the two-party scenario, but multi-party dialogues are pervasive in reality. |
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Modelling Context Emotions using Multi-task Learning for Emotion Controlled Dialog Generation (2021.eacl-main)
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| Challenge: | Recent research has tackled this task using neural generative methods by augmenting emotion classes with the input sequences. |
| Approach: | They propose to use a self-attention based encoder and a decoder with dot product attention mechanism to generate a viable response with a specified emotion. |
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Emotional Speech Corpus for Persuasive Dialogue System (2020.lrec-1)
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| Challenge: | Emotional expressions can be used to express the speaker’s emotion more directly than using only emotion expression in the text. |
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REG: Retrieval via Emotion Similarity for Guiding Empathetic Dialogue Generation (2026.acl-long)
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| Challenge: | Empathy relies on the cognitive capacity to relate to similar past experiences. Existing methods prioritize semantic similarity over emotion characteristics, leading to unempathetic responses. |
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MojiTalk: Generating Emotional Responses at Scale (P18-1)
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| Challenge: | Existing studies on emotion-generating systems focus on small sets of labeled datasets. |
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