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        <title>Interaction Quality Estimation Using Long Short-Term Memories</title>
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            <title>Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue</title>
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            <namePart type="given">Kristiina</namePart>
            <namePart type="family">Jokinen</namePart>
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            <namePart type="given">Manfred</namePart>
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    <abstract>For estimating the Interaction Quality (IQ) in Spoken Dialogue Systems (SDS), the dialogue history is of significant importance. Previous works included this information manually in the form of precomputed temporal features into the classification process. Here, we employ a deep learning architecture based on Long Short-Term Memories (LSTM) to extract this information automatically from the data, thus estimating IQ solely by using current exchange features. We show that it is thereby possible to achieve competitive results as in a scenario where manually optimized temporal features have been included.</abstract>
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%0 Conference Proceedings
%T Interaction Quality Estimation Using Long Short-Term Memories
%A Rach, Niklas
%A Minker, Wolfgang
%A Ultes, Stefan
%Y Jokinen, Kristiina
%Y Stede, Manfred
%Y DeVault, David
%Y Louis, Annie
%S Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
%D 2017
%8 August
%I Association for Computational Linguistics
%C Saarbrücken, Germany
%F rach-etal-2017-interaction
%X For estimating the Interaction Quality (IQ) in Spoken Dialogue Systems (SDS), the dialogue history is of significant importance. Previous works included this information manually in the form of precomputed temporal features into the classification process. Here, we employ a deep learning architecture based on Long Short-Term Memories (LSTM) to extract this information automatically from the data, thus estimating IQ solely by using current exchange features. We show that it is thereby possible to achieve competitive results as in a scenario where manually optimized temporal features have been included.
%R 10.18653/v1/W17-5520
%U https://aclanthology.org/W17-5520
%U https://doi.org/10.18653/v1/W17-5520
%P 164-169

Markdown (Informal)

[Interaction Quality Estimation Using Long Short-Term Memories](https://aclanthology.org/W17-5520) (Rach et al., SIGDIAL 2017)

• Interaction Quality Estimation Using Long Short-Term Memories (Rach et al., SIGDIAL 2017)

ACL

• Niklas Rach, Wolfgang Minker, and Stefan Ultes. 2017. Interaction Quality Estimation Using Long Short-Term Memories. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, pages 164–169, Saarbrücken, Germany. Association for Computational Linguistics.