@inproceedings{navarretta-lis-2014-transfer,
title = "Transfer learning of feedback head expressions in {D}anish and {P}olish comparable multimodal corpora",
author = "Navarretta, Costanza and
Lis, Magdalena",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/525_Paper.pdf",
pages = "3597--3603",
abstract = {The paper is an investigation of the reusability of the annotations of head movements in a corpus in a language to predict the feedback functions of head movements in a comparable corpus in another language. The two corpora consist of naturally occurring triadic conversations in Danish and Polish, which were annotated according to the same scheme. The intersection of common annotation features was used in the experiments. A Na{\"\i}ve Bayes classifier was trained on the annotations of a corpus and tested on the annotations of the other corpus. Training and test datasets were then reversed and the experiments repeated. The results show that the classifier identifies more feedback behaviours than the majority baseline in both cases and the improvements are significant. The performance of the classifier decreases significantly compared with the results obtained when training and test data belong to the same corpus. Annotating multimodal data is resource consuming, thus the results are promising. However, they also confirm preceding studies that have identified both similarities and differences in the use of feedback head movements in different languages. Since our datasets are small and only regard a communicative behaviour in two languages, the experiments should be tested on more data types.},
}
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<abstract>The paper is an investigation of the reusability of the annotations of head movements in a corpus in a language to predict the feedback functions of head movements in a comparable corpus in another language. The two corpora consist of naturally occurring triadic conversations in Danish and Polish, which were annotated according to the same scheme. The intersection of common annotation features was used in the experiments. A Naïve Bayes classifier was trained on the annotations of a corpus and tested on the annotations of the other corpus. Training and test datasets were then reversed and the experiments repeated. The results show that the classifier identifies more feedback behaviours than the majority baseline in both cases and the improvements are significant. The performance of the classifier decreases significantly compared with the results obtained when training and test data belong to the same corpus. Annotating multimodal data is resource consuming, thus the results are promising. However, they also confirm preceding studies that have identified both similarities and differences in the use of feedback head movements in different languages. Since our datasets are small and only regard a communicative behaviour in two languages, the experiments should be tested on more data types.</abstract>
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%0 Conference Proceedings
%T Transfer learning of feedback head expressions in Danish and Polish comparable multimodal corpora
%A Navarretta, Costanza
%A Lis, Magdalena
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F navarretta-lis-2014-transfer
%X The paper is an investigation of the reusability of the annotations of head movements in a corpus in a language to predict the feedback functions of head movements in a comparable corpus in another language. The two corpora consist of naturally occurring triadic conversations in Danish and Polish, which were annotated according to the same scheme. The intersection of common annotation features was used in the experiments. A Naïve Bayes classifier was trained on the annotations of a corpus and tested on the annotations of the other corpus. Training and test datasets were then reversed and the experiments repeated. The results show that the classifier identifies more feedback behaviours than the majority baseline in both cases and the improvements are significant. The performance of the classifier decreases significantly compared with the results obtained when training and test data belong to the same corpus. Annotating multimodal data is resource consuming, thus the results are promising. However, they also confirm preceding studies that have identified both similarities and differences in the use of feedback head movements in different languages. Since our datasets are small and only regard a communicative behaviour in two languages, the experiments should be tested on more data types.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/525_Paper.pdf
%P 3597-3603
Markdown (Informal)
[Transfer learning of feedback head expressions in Danish and Polish comparable multimodal corpora](http://www.lrec-conf.org/proceedings/lrec2014/pdf/525_Paper.pdf) (Navarretta & Lis, LREC 2014)
ACL