no code implementations • SIGDIAL (ACL) 2020 • Stefan Ultes, Wolfgang Maier
The differences in decision making between behavioural models of voice interfaces are hard to capture using existing measures for the absolute performance of such models.
no code implementations • SIGDIAL (ACL) 2021 • Stefan Ultes, Wolfgang Maier
Recently, principal reward components for dialogue policy reinforcement learning use task success and user satisfaction independently and neither the resulting learned behaviour has been analysed nor a suitable proper analysis method even existed.
no code implementations • 6 Aug 2023 • Ye Liu, Stefan Ultes, Wolfgang Minker, Wolfgang Maier
In this work, we study dialogue scenarios that start from chit-chat but eventually switch to task-related services, and investigate how a unified dialogue model, which can engage in both chit-chat and task-oriented dialogues, takes the initiative during the dialogue mode transition from chit-chat to task-oriented in a coherent and cooperative manner.
no code implementations • 4 Jul 2023 • Ye Liu, Stefan Ultes, Wolfgang Minker, Wolfgang Maier
We contribute two efficient prompt models which can proactively generate a transition sentence to trigger system-initiated transitions in a unified dialogue model.
no code implementations • 29 Sep 2022 • Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes
The pre-trained conversational models still fail to capture the implicit commonsense (CS) knowledge hidden in the dialogue interaction, even though they were pre-trained with an enormous dataset.
no code implementations • ICON 2021 • Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes
We utilize the pre-trained multi-context ConveRT model for context representation in a model trained from scratch; and leverage the immediate preceding user utterance for context generation in a model adapted from the pre-trained GPT-2.
no code implementations • 7 Sep 2021 • Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes
One challenge for dialogue agents is to recognize feelings of the conversation partner and respond accordingly.
no code implementations • RANLP 2021 • Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes
This paper presents an automatic method to evaluate the naturalness of natural language generation in dialogue systems.
no code implementations • WS 2018 • Mohammed Attia, Younes Samih, Wolfgang Maier
This paper describes our system submission to the CALCS 2018 shared task on named entity recognition on code-switched data for the language variant pair of Modern Standard Arabic and Egyptian dialectal Arabic.
no code implementations • SEMEVAL 2018 • Mohammed Attia, Younes Samih, Manaal Faruqui, Wolfgang Maier
This paper describes our system submission to the SemEval 2018 Task 10 on Capturing Discriminative Attributes.
no code implementations • WS 2017 • Patricia Braunger, Wolfgang Maier
By means of a comparative study of the utterances from the study with interpersonal utterances, we provide criteria what constitutes naturalness in the user input of an state-of-the-art automotive SDS.
no code implementations • LREC 2016 • Younes Samih, Wolfgang Maier
In this paper, we describe our effort in the development and annotation of a large scale corpus containing code-switched data.
no code implementations • LREC 2014 • Wolfgang Maier, Miriam Kaeshammer, Peter Baumann, S K{\"u}bler, ra
However, for the evaluation of parser performance concerning a particular phenomenon, a test suite of sentences is needed in which this phenomenon has been identified.
no code implementations • WS 2013 • Djam{\'e} Seddah, Reut Tsarfaty, S K{\"u}bler, ra, C, Marie ito, Jinho D. Choi, Rich{\'a}rd Farkas, Jennifer Foster, Iakes Goenaga, Koldo Gojenola Galletebeitia, Yoav Goldberg, Spence Green, Nizar Habash, Marco Kuhlmann, Wolfgang Maier, Joakim Nivre, Adam Przepi{\'o}rkowski, Ryan Roth, Wolfgang Seeker, Yannick Versley, Veronika Vincze, Marcin Woli{\'n}ski, Alina Wr{\'o}blewska, Eric Villemonte de la Clergerie