Papers by Shumpei Inoue
Enhance Incomplete Utterance Restoration by Joint Learning Token Extraction and Text Generation (2022.naacl-main)
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| Challenge: | omitted tokens from the context contribute to incomplete utterance restoration (IUR) understanding conversational interactions through NLP has become important with increasing connectivity and range of capabilities. |
| Approach: | They propose a model for incomplete utterance restoration called JET . they construct a Picker that identifies omitted tokens and two label creation methods to support the picker. |
| Outcome: | The proposed model is better than pretrained T5 and non-generative language model methods on four benchmark datasets in extraction and abstraction scenarios. |
Meeting Decision Tracker: Making Meeting Minutes with De-Contextualized Utterances (2022.aacl-demo)
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| Challenge: | Existing systems to itemize meetings' decisions are lacking in their raw form due to utterance collapse. |
| Approach: | They propose a prototype system to construct decision items that deal with utterance collapse in natural conversation. |
| Outcome: | The proposed system improves the user experience by dealing with utterance collapse in natural conversation. |
Towards Safer Operations: An Expert-involved Dataset of High-Pressure Gas Incidents for Preventing Future Failures (2023.emnlp-industry)
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| Challenge: | Existing datasets for incident management tasks are labor-intensive and time-consuming. |
| Approach: | They propose a new IncidentAI dataset for safety prevention that includes three tasks . they argue that NLP techniques are beneficial for analyzing incident reports . |
| Outcome: | The proposed dataset shows that NLP techniques are beneficial for analyzing incident reports to prevent future failures. |