Graph Integrated Language Transformers for Next Action Prediction in Complex Phone Calls

Amin Marani, Ulie Schnaithmann, Youngseo Son, Akil Iyer, Manas Paldhe, Arushi Raghuvanshi

Abstract
Current Conversational AI systems employ different machine learning pipelines, as well as external knowledge sources and business logic to predict the next action. Maintaining various components in dialogue managers’ pipeline adds complexity in expansion and updates, increases processing time, and causes additive noise through the pipeline that can lead to incorrect next action prediction. This paper investigates graph integration into language transformers to improve understanding the relationships between humans’ utterances, previous, and next actions without the dependency on external sources or components. Experimental analyses on real calls indicate that the proposed Graph Integrated Language Transformer models can achieve higher performance compared to other production level conversational AI systems in driving interactive calls with human users in real-world settings.
Anthology ID:
2024.naacl-industry.29
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Yi Yang, Aida Davani, Avi Sil, Anoop Kumar
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
347–358
Language:
URL:
https://aclanthology.org/2024.naacl-industry.29
DOI:
10.18653/v1/2024.naacl-industry.29
Bibkey:
Cite (ACL):
Amin Marani, Ulie Schnaithmann, Youngseo Son, Akil Iyer, Manas Paldhe, and Arushi Raghuvanshi. 2024. Graph Integrated Language Transformers for Next Action Prediction in Complex Phone Calls. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track), pages 347–358, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Graph Integrated Language Transformers for Next Action Prediction in Complex Phone Calls (Marani et al., NAACL 2024)
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PDF:
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