Andy Luecking


2022

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I still have Time(s): Extending HeidelTime for German Texts
Andy Luecking | Manuel Stoeckel | Giuseppe Abrami | Alexander Mehler
Proceedings of the Thirteenth Language Resources and Evaluation Conference

HeidelTime is one of the most widespread and successful tools for detecting temporal expressions in texts. Since HeidelTime’s pattern matching system is based on regular expression, it can be extended in a convenient way. We present such an extension for the German resources of HeidelTime: HeidelTimeExt. The extension has been brought about by means of observing false negatives within real world texts and various time banks. The gain in coverage is 2.7 % or 8.5 %, depending on the admitted degree of potential overgeneralization. We describe the development of HeidelTimeExt, its evaluation on text samples from various genres, and share some linguistic observations. HeidelTimeExt can be obtained from https://github.com/texttechnologylab/heideltime.

2021

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Requesting clarifications with speech and gestures
Jonathan Ginzburg | Andy Luecking
Proceedings of the 1st Workshop on Multimodal Semantic Representations (MMSR)

In multimodal natural language interaction both speech and non-speech gestures are involved in the basic mechanism of grounding and repair. We discuss a couple of multimodal clarifica- tion requests and argue that gestures, as well as speech expressions, underlie comparable paral- lelism constraints. In order to make this precise, we slightly extend the formal dialogue frame- work KoS to cover also gestural counterparts of verbal locutionary propositions.

2016

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Finding Recurrent Features of Image Schema Gestures: the FIGURE corpus
Andy Luecking | Alexander Mehler | Désirée Walther | Marcel Mauri | Dennis Kurfürst
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The Frankfurt Image GestURE corpus (FIGURE) is introduced. The corpus data is collected in an experimental setting where 50 naive participants spontaneously produced gestures in response to five to six terms from a total of 27 stimulus terms. The stimulus terms have been compiled mainly from image schemata from psycholinguistics, since such schemata provide a panoply of abstract contents derived from natural language use. The gestures have been annotated for kinetic features. FIGURE aims at finding (sets of) stable kinetic feature configurations associated with the stimulus terms. Given such configurations, they can be used for designing HCI gestures that go beyond pre-defined gesture vocabularies or touchpad gestures. It is found, for instance, that movement trajectories are far more informative than handshapes, speaking against purely handshape-based HCI vocabularies. Furthermore, the mean temporal duration of hand and arm movements associated vary with the stimulus terms, indicating a dynamic dimension not covered by vocabulary-based approaches. Descriptive results are presented and related to findings from gesture studies and natural language dialogue.

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TGermaCorp – A (Digital) Humanities Resource for (Computational) Linguistics
Andy Luecking | Armin Hoenen | Alexander Mehler
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

TGermaCorp is a German text corpus whose primary sources are collected from German literature texts which date from the sixteenth century to the present. The corpus is intended to represent its target language (German) in syntactic, lexical, stylistic and chronological diversity. For this purpose, it is hand-annotated on several linguistic layers, including POS, lemma, named entities, multiword expressions, clauses, sentences and paragraphs. In order to introduce TGermaCorp in comparison to more homogeneous corpora of contemporary everyday language, quantitative assessments of syntactic and lexical diversity are provided. In this respect, TGermaCorp contributes to establishing characterising features for resource descriptions, which is needed for keeping track of a meaningful comparison of the ever-growing number of natural language resources. The assessments confirm the special role of proper names, whose propagation in text may influence lexical and syntactic diversity measures in rather trivial ways. TGermaCorp will be made available via hucompute.org.