Papers by Sean Robertson
Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service Support (2022.emnlp-industry)
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Stephen Obadinma, Faiza Khan Khattak, Shirley Wang, Tania Sidhorn, Elaine Lau, Sean Robertson, Jingcheng Niu, Winnie Au, Alif Munim, Karthik Raja Kalaiselvi Bhaskar
| Challenge: | Creating agent assistants that can help improve customer service support requires inputs from industry users and their customers as well as knowledge of state-of-the-art natural language processing (NLP) technology. |
| Approach: | They propose to combine expertise from academia and industry to build task/domain-specific Neural Agent Assistants with three high-level components for: (1) Intent Identification, (2) Context Retrieval, and (3) Response Generation. |
| Outcome: | The proposed framework is based on three case studies of industry partners who successfully adapt the framework to their unique challenges. |
FAB: The French Absolute Beginner Corpus for Pronunciation Training (2020.lrec-1)
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| Challenge: | French Absolute Beginner corpus is intended for the development and study of Computer-Assisted Pronunciation Training (CAPT) tools for absolute beginner learners. |
| Approach: | They introduce the French Absolute Beginner (FAB) speech corpus which is intended for the development and study of Computer-Assisted Pronunciation Training tools for absolute beginner learners. |
| Outcome: | The proposed corpus is intended for the development and study of Computer-Assisted Pronunciation Training tools for absolute beginner learners. |