| Challenge: | Existing task frameworks for dialog-act classification and slot filling can only interpret utterances using pre-defined types and slots. |
| Approach: | They propose a task to describe the intent of an utterance in a dialog with multiple simple natural sentences without the context. |
| Outcome: | The proposed task can describe the intent of an utterance in a dialog with multiple simple natural sentences without the context. |
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| Challenge: | In Japan, the number of single-person households is increasing, reducing opportunities for people to narrate. |
| Approach: | They propose to collect 148,962 responsive utterances by listeners and annotate existing narrative speech with responsive . they also propose to use robots and smart speakers to listen to narratives . |
| Outcome: | The proposed method can be used to annotate existing narrative speech with responsive utterances. |
JDCFC: A Japanese Dialogue Corpus with Feature Changes (L18-1)
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| Challenge: | Existing corpora focus on emotional expressions in conversations, but there are no large-scale corpors focusing on the relationships between emotions and utterances. |
| Approach: | They propose a Japanese Feature Change Knowledge Base (JFCKB) that focuses on emotional expressions in conversations. |
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DIRECT: Direct and Indirect Responses in Conversational Text Corpus (2021.findings-emnlp)
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| Challenge: | Neural conversation models have been able to generate fluent responses through training on a dialogue corpus, but they lack the ability to reveal the implied intentions of users. |
| Approach: | They propose to train neural conversation models on a dialogue corpus that provides pragmatic paraphrases to advance techniques for natural language understanding in dialogue systems. |
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Predicting Nods by using Dialogue Acts in Dialogue (L18-1)
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| Challenge: | Existing studies have generated nods from the final morphemes at the end of an utterance. |
| Approach: | They propose to generate head nods from Japanese dialogues using morphemes . they compile a corpus of 24 dialogues including utterance and nod information . |
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Construction and Analysis of a Multimodal Chat-talk Corpus for Dialog Systems Considering Interpersonal Closeness (2020.lrec-1)
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| Challenge: | a large-scale multimodal dialog corpus is needed to accelerate research on dialog systems that can handle social signals and verbal information. |
| Approach: | They construct a multimodal dialog corpus focusing on the relationship between speakers and 19 pairs of participants. |
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Construction of the Corpus of Everyday Japanese Conversation: An Interim Report (L18-1)
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Hanae Koiso, Yasuharu Den, Yuriko Iseki, Wakako Kashino, Yoshiko Kawabata, Ken’ya Nishikawa, Yayoi Tanaka, Yasuyuki Usuda
| Challenge: | a new corpus of everyday conversations is being developed in the field of everyday conversation . the corpus is based on 94 hours of recordings of everyday Japanese conversations . |
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The JDDC Corpus: A Large-Scale Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service (2020.lrec-1)
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| Challenge: | Existing datasets for human-like dialogue tasks are deficient due to the complexity of human conversations. |
| Approach: | They construct a large-scale Chinese E-commerce conversation corpus with 1 million dialogues, 20 million utterances, and 150 million words. |
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Japanese Dialogue Corpus of Information Navigation and Attentive Listening Annotated with Extended ISO-24617-2 Dialogue Act Tags (L18-1)
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| Challenge: | Large-scale conventional dialogue corpora are mainly built for specified tasks with specially designed dialogue states. |
| Approach: | They propose to annotate large-scale dialogue data with an extended ISO-24617-2 dialogue act tag-set to model a natural conversation with machines. |
| Outcome: | The proposed corpus covers a wider range of dialogue tasks than existing task-oriented systems or text-chat systems. |
Machines Getting with the Program: Understanding Intent Arguments of Non-Canonical Directives (2020.findings-emnlp)
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| Challenge: | Modern dialog managers face the challenge of having to fulfill human-level conversational skills as part of common user expectations. |
| Approach: | They propose to extract the intent argument of non-canonical directives in a natural language format and build a parallel corpus for this purpose. |
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JAIST Annotated Corpus of Free Conversation (L18-1)
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| Challenge: | Annotated corpus of free conversations in Japanese is the first publicly available one. |
| Approach: | They propose to annotate free conversations in Japanese with dialog act and sympathy tags . they report how to construct the corpus and its statistics . |
| Outcome: | The proposed corpus is the first annotated corpus of free conversations in Japanese . it consists of 92,031 utterances in 97 dialogs. |