Jan Nehring


2023

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Context-Aware Module Selection in Modular Dialog Systems
Jan Nehring | René Marcel Berk | Stefan Hillmann
Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing

In modular dialog systems, a dialog system consists of multiple conversational agents. The task “module selection” selects the appropriate sub-dialog system for an incoming user utterance. Current models for module selection use features derived from the current user turn only, such as the utterances text or confidence values of the natural language understanding systems of the individual conversational agents, or they perform text classification on the user utterance. However, dialogs often span multiple turns, and turns are embedded into a context. Therefore, looking at the current user turn only is a source of error in certain situations. This work proposes four models for module selection that include the dialog history and the current user turn into module selection. We show that these models surpass the current state of the art in module selection.

2021

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Combining Open Domain Question Answering with a Task-Oriented Dialog System
Jan Nehring | Nils Feldhus | Harleen Kaur | Akhyar Ahmed
Proceedings of the 1st Workshop on Document-grounded Dialogue and Conversational Question Answering (DialDoc 2021)

We apply the modular dialog system framework to combine open-domain question answering with a task-oriented dialog system. This meta dialog system can answer questions from Wikipedia and at the same time act as a personal assistant. The aim of this system is to combine the strength of an open-domain question answering system with the conversational power of task-oriented dialog systems. After explaining the technical details of the system, we combined a new dataset out of standard datasets to evaluate the system. We further introduce an evaluation method for this system. Using this method, we compare the performance of the non-modular system with the performance of the modular system and show that the modular dialog system framework is very suitable for this combination of conversational agents and that the performance of each agent decreases only marginally through the modular setting.

2018

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A Framework for the Needs of Different Types of Users in Multilingual Semantic Enrichment
Jan Nehring | Felix Sasaki
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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Event Detection and Semantic Storytelling: Generating a Travelogue from a large Collection of Personal Letters
Georg Rehm | Julian Moreno Schneider | Peter Bourgonje | Ankit Srivastava | Jan Nehring | Armin Berger | Luca König | Sören Räuchle | Jens Gerth
Proceedings of the Events and Stories in the News Workshop

We present an approach at identifying a specific class of events, movement action events (MAEs), in a data set that consists of ca. 2,800 personal letters exchanged by the German architect Erich Mendelsohn and his wife, Luise. A backend system uses these and other semantic analysis results as input for an authoring environment that digital curators can use to produce new pieces of digital content. In our example case, the human expert will receive recommendations from the system with the goal of putting together a travelogue, i.e., a description of the trips and journeys undertaken by the couple. We describe the components and architecture and also apply the system to news data.

2016

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How to configure statistical machine translation with linked open data resources
Ankit Srivastava | Felix Sasaki | Peter Bourgonje. Julian Moreno-Schneider | Jan Nehring | Georg Rehm
Proceedings of Translating and the Computer 38