Papers by Yanchao Yu
How Much Do Robots Understand Rudeness? Challenges in Human-Robot Interaction (2024.lrec-main)
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| Challenge: | This paper examines the pressing need to understand and manage inappropriate language within the evolving human-robot interaction landscape. |
| Approach: | They propose to use data cleaning methods to identify inappropriate language in real-time interactions and evaluate natural language models for their proficiency in discerning rudeness. |
| Outcome: | The proposed methods identify and mitigate inappropriate language in real-time interactions and evaluate natural language models for their proficiency in discerning rudeness. |
A Comprehensive Evaluation of Incremental Speech Recognition and Diarization for Conversational AI (2020.coling-main)
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| Challenge: | Automatic Speech Recognition (ASR) systems are increasingly powerful and more numerous with several options existing as a service. |
| Approach: | They evaluate the most popular automatic speech recognition systems with metrics and experiments designed with these standards in mind. |
| Outcome: | The most popular ASR systems are Microsoft and IBM, and none are suitable for natural spontaneous conversations in real-time. |
The CRECIL Corpus: a New Dataset for Extraction of Relations between Characters in Chinese Multi-party Dialogues (2022.lrec-1)
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Yuru Jiang, Yang Xu, Yuhang Zhan, Weikai He, Yilin Wang, Zixuan Xi, Meiyun Wang, Xinyu Li, Yu Li, Yanchao Yu
| Challenge: | Existing datasets focus on relation extraction between two entities in one sentence, and some focus on cross-sentence relationships. |
| Approach: | They propose to use a Chinese multi-party dialogue dataset for automatic extraction of dialogue-based character relationships. |
| Outcome: | The proposed dataset extracts relationships between 140 entities on the CRECIL corpus and another existing relation extraction corpus. |