In the Natural Language Generation field, Referring Expression Generation (REG) studies often make use of experiments involving human subjects for the collection of corpora of definite descriptions. Experiments of this kind usually make use of web-based settings in which a single subject acts as a speaker with no particular addressee in mind (as a kind of monologue situation), or in which participant pairs are engaged in an actual dialogue. Both so-called monologue and dialogue settings are of course instances of real language use, but it is not entirely clear whether these situations are truly comparable or, to be more precise, whether REG studies may draw conclusions regarding attribute selection, referential overspecification and others regardless of the mode of communication. To shed light on this issue, in this work we developed a parallel, semantically annotated corpus of monologue and dialogue referring expressions, and carried out an experiment to compare instances produced in both modes of communication. Preliminary results suggest that human reference production may be indeed affected by the presence of a second (specific) human participant as the receiver of the communication in a number of ways, an observation that may be relevant for studies in REG and related fields.
@InProceedings{ROCHA18.4, author = {Danillo Rocha and Ivandré Paraboni}, title = "{Reference production in human-computer interaction: Issues for Corpus-based Referring Expression Generation}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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