Predicting Interaction Quality of Conversational Assistants With Spoken Language Understanding Model Confidences

Author:

Gao Yue1ORCID,Piovano Enrico2ORCID,Soliman Tamer3ORCID,Moniruzzaman Monir4ORCID,Kumar Anoop4ORCID,Bradford Melanie2ORCID,Nandi Subhrangshu4ORCID

Affiliation:

1. University of Wisconsin-Madison, Madison, USA

2. Amazon Alexa AI, Berlin, Germany

3. Amazon Alexa AI, Sunnyvale, USA

4. Amazon Alexa AI, Seattle, USA

Publisher

ACM

Reference28 articles.

1. Praveen Kumar Bodigutla , Spyros Matsoukas , Longshaokan Marshall Wang , Kate Ridgeway , Joshua Levy , Swanand Joshi , and Alborz Geramifard . 2019 . Domain-Independent turn-level Dialogue Quality Evaluation via User Satisfaction Estimation . In SIGDIAL 2019 Workshop on Implications of Deep Learning for Dialog Modeling. Praveen Kumar Bodigutla, Spyros Matsoukas, Longshaokan Marshall Wang, Kate Ridgeway, Joshua Levy, Swanand Joshi, and Alborz Geramifard. 2019. Domain-Independent turn-level Dialogue Quality Evaluation via User Satisfaction Estimation. In SIGDIAL 2019 Workshop on Implications of Deep Learning for Dialog Modeling.

2. Joint Turn and Dialogue level User Satisfaction Estimation on Multi-Domain Conversations

3. Error Detection in Large-Scale Natural Language Understanding Systems Using Transformer Models

4. Sample Selection Bias Correction Theory

5. Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2019 . BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding . In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, 4171--4186. https://doi.org/10. 18653/v1/N19--1423 10.18653/v1 Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, 4171--4186. https://doi.org/10.18653/v1/N19--1423

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