@inproceedings{ffc19bc5d2b74c06bea252aaa18346ce,
title = "Rating Prediction in Conversational Task Assistants with Behavioral and Conversational-Flow Features",
abstract = "Predicting the success of Conversational Task Assistants (CTA) can be critical to understand user behavior and act accordingly. In this paper, we propose TB-Rater, a Transformer model which combines conversational-flow features with user behavior features for predicting user ratings in a CTA scenario. In particular, we use real human-agent conversations and ratings collected in the Alexa TaskBot challenge, a novel multimodal and multi-turn conversational context. Our results show the advantages of modeling both the conversational-flow and behavioral aspects of the conversation in a single model for offline rating prediction. Additionally, an analysis of the CTA-specific behavioral features brings insights into this setting and can be used to bootstrap future systems.",
keywords = "Conversational Task Assistants, NLP, Rating Prediction",
author = "Rafael Ferreira and David Semedo and Jo{\~a}o Magalh{\~a}es",
note = "Funding Information: info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04516%2F2020/PT# This work has been partially funded by FCT Ref UI/BD/151261/2021, and by the CMU| Portugal iFetch project LISBOA-01-0247-FEDER-045920. Publisher Copyright: {\textcopyright} 2023 Copyright held by the owner/author(s).; 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023 ; Conference date: 23-07-2023 Through 27-07-2023",
year = "2023",
month = jul,
day = "19",
doi = "10.1145/3539618.3592048",
language = "English",
isbn = " 978-1-4503-9408-6",
series = "IR: Research and Development in Information Retrieval",
publisher = "ACM - Association for Computing Machinery",
pages = "2314--2318",
booktitle = "SIGIR 2023",
address = "United States",
}