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A bathtub by any other name: the reduction of German compounds in predictive contexts
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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A bathtub by any other name: the reduction of German compounds in predictive contexts ...
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Crowdsourcing Ecologically-Valid Dialogue Data for German
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In: Fraunhofer IIS (2021)
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Not so Fast, Classifier - Accuracy and Entropy Reduction in Incremental Intent Classification
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In: Fraunhofer IIS (2021)
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New Domain, Major Effort? How Much Data is Necessary to Adapt a Temporal Tagger to the Voice Assistant Domain
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In: Fraunhofer IIS (2021)
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Small Data in NLU: Proposals towards a Data-Centric Approach: Paper presented at 35th Conference on Neural Information Processing Systems, NeurIPS 2021, Sydney, Australia, Virtual-only Conference
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In: Fraunhofer IIS ; Fraunhofer IAIS (2021)
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Abstract:
Domain-specific voice assistants often suffer from the problem of data scarcity. Publicly available, annotated datasets are in short supply and rarely fit the domain and the language required by a specific use case. Insufficient attention to data quality can generally be problematic when it comes to training and evaluation. The Computational Linguistics (CL) community has gained expertise and developed best practices for high-quality data annotation and collection as well as for for qualitative data analysis. However, the recent model-centric focus in AI and ML has not created ideal conditions for a fruitful collaboration with CL and the more data-centric fields of NLP to tackle data quality issues. We showcase principles and methods from CL / NLP research, which can potentially guide the development of data-centric NLU for domain-specific voice assistants - but have been typically overlooked by common practices in ML / AI. Those principles can potentially be of help to shape data-centric practices also for other domains. We argue that paying more attention to data quality and domain specificity can go a long way in improving the NLU components of todays voice assistants.
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URL: http://publica.fraunhofer.de/documents/N-647727.html
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PATE: A corpus of temporal expressions for the in-car voice assistant domain
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In: Fraunhofer IIS (2020)
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Complement Coercion: The Joint Effects of Type and Typicality
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In: Psychology Publications (2017)
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Event knowledge and models of logical metonymy interpretation ... : Ereigniswissen und Modelle der Interpretation logischer Metonymie ...
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Event knowledge and models of logical metonymy interpretation ; Ereigniswissen und Modelle der Interpretation logischer Metonymie
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Aktionsarten, speech and gesture
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In: Proceedings of GESPIN2011: Gesture and speech in interaction ; GESPIN 2011 : Gesture and Speech in Interaction ; https://hal.parisnanterre.fr//hal-03111513 ; GESPIN 2011 : Gesture and Speech in Interaction, Sep 2011, Bielefeld, Germany ; http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=14912©ownerid=1 (2011)
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