Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service Support
Abstrak
Building Agent Assistants that can help improve customer service support requires inputs from industry users and their customers, as well as knowledge about state-of-the-art Natural Language Processing (NLP) technology. We combine expertise from academia and industry to bridge the gap and build task/domain-specific Neural Agent Assistants (NAA) with three high-level components for: (1) Intent Identification, (2) Context Retrieval, and (3) Response Generation. In this paper, we outline the pipeline of the NAA's core system and also present three case studies in which three industry partners successfully adapt the framework to find solutions to their unique challenges. Our findings suggest that a collaborative process is instrumental in spurring the development of emerging NLP models for Conversational AI tasks in industry. The full reference implementation code and results are available at \url{https://github.com/VectorInstitute/NAA}
Topik & Kata Kunci
Penulis (26)
Stephen Obadinma
Faiza Khan Khattak
Shirley Wang
Tania Sidhom
Elaine Lau
Sean Robertson
Jingcheng Niu
Winnie Au
Alif Munim
Karthik Raja K. Bhaskar
Bencheng Wei
Iris Ren
Waqar Muhammad
Erin Li
Bukola Ishola
Michael Wang
Griffin Tanner
Yu-Jia Shiah
Sean X. Zhang
Kwesi P. Apponsah
Kanishk Patel
Jaswinder Narain
Deval Pandya
Xiaodan Zhu
Frank Rudzicz
Elham Dolatabadi
Akses Cepat
- Tahun Terbit
- 2023
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓