{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:35:42Z","timestamp":1760240142664,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,3,3]],"date-time":"2019-03-03T00:00:00Z","timestamp":1551571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Automatic dialog act recognition is an important step for dialog systems since it reveals the intention behind the words uttered by its conversational partners. Although most approaches on the task use word-level tokenization, there is information at the sub-word level that is related to the function of the words and, consequently, their intention. Thus, in this study, we explored the use of character-level tokenization to capture that information. We explored the use of multiple character windows of different sizes to capture morphological aspects, such as affixes and lemmas, as well as inter-word information. Furthermore, we assessed the importance of punctuation and capitalization for the task. To broaden the conclusions of our study, we performed experiments on dialogs in three languages\u2014English, Spanish, and German\u2014which have different morphological characteristics. Furthermore, the dialogs cover multiple domains and are annotated with both domain-dependent and domain-independent dialog act labels. The achieved results not only show that the character-level approach leads to similar or better performance than the state-of-the-art word-level approaches on the task, but also that both approaches are able to capture complementary information. Thus, the best results are achieved by combining tokenization at both levels.<\/jats:p>","DOI":"10.3390\/info10030094","type":"journal-article","created":{"date-parts":[[2019,3,4]],"date-time":"2019-03-04T05:45:36Z","timestamp":1551678336000},"page":"94","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Multilingual and Multidomain Study on Dialog Act Recognition Using Character-Level Tokenization"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7147-8675","authenticated-orcid":false,"given":"Eug\u00e9nio","family":"Ribeiro","sequence":"first","affiliation":[{"name":"L<sup>2<\/sup>F\u2014Spoken Language Systems Laboratory\u2014INESC-ID, 1000-029 Lisboa, Portugal"},{"name":"Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2058-693X","authenticated-orcid":false,"given":"Ricardo","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"L<sup>2<\/sup>F\u2014Spoken Language Systems Laboratory\u2014INESC-ID, 1000-029 Lisboa, Portugal"},{"name":"Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8631-2870","authenticated-orcid":false,"given":"David Martins","family":"de Matos","sequence":"additional","affiliation":[{"name":"L<sup>2<\/sup>F\u2014Spoken Language Systems Laboratory\u2014INESC-ID, 1000-029 Lisboa, Portugal"},{"name":"Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Searle, J.R. (1969). Speech Acts: An Essay in the Philosophy of Language, Cambridge University Press.","DOI":"10.1017\/CBO9781139173438"},{"key":"ref_2","first-page":"227","article-title":"Dialogue Act Recognition Approaches","volume":"29","author":"Cerisara","year":"2010","journal-title":"Comput. Inform."},{"key":"ref_3","unstructured":"Kalchbrenner, N., and Blunsom, P. (2013, January 9). Recurrent Convolutional Neural Networks for Discourse Compositionality. Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality, Sofia, Bulgaria."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Lee, J.Y., and Dernoncourt, F. (2016, January 12\u201317). Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016), Diego, CA, USA.","DOI":"10.18653\/v1\/N16-1062"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ji, Y., Haffari, G., and Eisenstein, J. (2016, January 12\u201317). A Latent Variable Recurrent Neural Network for Discourse Relation Language Models. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016), Diego, CA, USA.","DOI":"10.18653\/v1\/N16-1037"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Liu, Y., Han, K., Tan, Z., and Lei, Y. (2017, January 7\u201311). Using Context Information for Dialog Act Classification in DNN Framework. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark.","DOI":"10.18653\/v1\/D17-1231"},{"key":"ref_7","unstructured":"Santos, C.D., and Zadrozny, B. (2014, January 21\u201326). Learning Character-level Representations for Part-of-Speech Tagging. Proceedings of the 31st International Conference on Machine Learning (ICML 2014), Beijing, China."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Jaech, A., Mulcaire, G., Hathi, S., Ostendorf, M., and Smith, N.A. (2016, January 11). Hierarchical Character-Word Models for Language Identification. Proceedings of the International Workshop on Natural Language Processing for Social Media, New York, NY, USA.","DOI":"10.18653\/v1\/W16-6212"},{"key":"ref_9","unstructured":"Zhang, X., Zhao, J., and LeCun, Y. (2015, January 7\u201312). Character-level Convolutional Networks for Text Classification. Proceedings of the Advances in Neural Information Processing Systems, Montreal, QC, Canada."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ribeiro, E., Ribeiro, R., and de Matos, D.M. (2018, January 2\u20137). A Study on Dialog Act Recognition using Character-Level Tokenization. Proceedings of the 18th International Conference on Artificial Intelligence: Methodology, Systems, Applications, San Francisco, CA, USA.","DOI":"10.1007\/978-3-319-99344-7_9"},{"key":"ref_11","unstructured":"Jurafsky, D., Shriberg, E., and Biasca, D. (1997). Switchboard SWBD-DAMSL Shallow-Discourse-Function Annotation Coders Manual, Institute of Cognitive Science, University of Colorado. Technical Report Draft 13."},{"key":"ref_12","unstructured":"Bened\u00ed, J.M., Lleida, E., Varona, A., Castro, M.J., Galiano, I., Justo, R., de Letona, I.L., and Miguel, A. (2006, January 22\u201328). Design and Acquisition of a Telephone Spontaneous Speech Dialogue Corpus in Spanish: DIHANA. Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC\u201906), Genoa, Italy."},{"key":"ref_13","unstructured":"Schmitt, A., Ultes, S., and Minker, W. (2012, January 21\u201327). A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let\u2019s Go Bus Information System. Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC), Istanbul, Turkey."},{"key":"ref_14","unstructured":"Kay, M., Norvig, P., and Gawron, M. (1992). VERBMOBIL: A Translation System for Face-to-Face Dialog, University of Chicago Press."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1162\/089120100561737","article-title":"Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech","volume":"26","author":"Stolcke","year":"2000","journal-title":"Comput. Linguist."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Gamb\u00e4ck, B., Olsson, F., and T\u00e4ckstr\u00f6m, O. (2011, January 27\u201331). Active Learning for Dialogue Act Classification. Proceedings of the 12th Annual Conference of the International Speech Communication Association (INTERSPEECH), Florence, Italy.","DOI":"10.21437\/Interspeech.2011-441"},{"key":"ref_17","unstructured":"Ribeiro, E., Ribeiro, R., and de Matos, D.M. (arXiv, 2015). The Influence of Context on Dialogue Act Recognition, arXiv."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1162\/COLI_a_00239","article-title":"Computational Linguistics and Deep Learning","volume":"41","author":"Manning","year":"2015","journal-title":"Comput. Linguist."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1613\/jair.4992","article-title":"A Primer on Neural Network Models for Natural Language Processing","volume":"57","author":"Goldberg","year":"2016","journal-title":"J. Artif. Intell. Res."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kim, S., D\u2019Haro, L.F., Banchs, R.E., Williams, J., and Henderson, M. (2016). The Fourth Dialog State Tracking Challenge. Dialogues with Social Robots, Springer.","DOI":"10.1109\/SLT.2016.7846311"},{"key":"ref_21","unstructured":"Janin, A., Baron, D., Edwards, J., Ellis, D., Gelbart, D., Morgan, N., Peskin, B., Pfau, T., Shriberg, E., and Stolcke, A. (2003, January 6\u201310). The ICSI Meeting Corpus. Proceedings of the 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Hong Kong, China."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Mikolov, T., Karafi\u00e1t, M., Burget, L., Cernock\u00fd, J., and Khudanpur, S. (2010, January 26\u201330). Recurrent Neural Network Based Language Model. Proceedings of the 11th Annual Conference of the International Speech Communication Association (INTERSPEECH), Chiba, Japan.","DOI":"10.21437\/Interspeech.2010-343"},{"key":"ref_23","unstructured":"Khanpour, H., Guntakandla, N., and Nielsen, R. (2016, January 11\u201316). Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network. Proceedings of the 26th International Conference on Computational Linguistics (COLING), Osaka, Japan."},{"key":"ref_24","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., and Dean, J. (2013, January 5\u201310). Distributed Representations of Words and Phrases and their Compositionality. Proceedings of the 26th International Conference on Neural Information Processing Systems (NIPS), Lake Tahoe, NV, USA."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., and Manning, C.D. (2014, January 25\u201329). GloVe: Global Vectors for Word Representation. Proceedings of the 2014 Conference on Empirical Methods on Natural Language Processing (EMNLP), Doha, Qatar.","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Godfrey, J.J., Holliman, E.C., and McDaniel, J. (1992, January 23\u201326). SWITCHBOARD: Telephone Speech Corpus for Research and Development. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), San Francisco, CA, USA.","DOI":"10.1109\/ICASSP.1992.225858"},{"key":"ref_27","first-page":"249","article-title":"Assessing Agreement on Classification Tasks: The Kappa Statistic","volume":"22","author":"Carletta","year":"1996","journal-title":"Comput. Linguist."},{"key":"ref_28","unstructured":"Rotaru, M. (2002). Dialog Act Tagging Using Memory-Based Learning, University of Pittsburgh. Technical Report."},{"key":"ref_29","unstructured":"Webb, N., and Ferguson, M. (2010, January 23\u201327). Automatic Extraction of Cue Phrases for Cross-corpus Dialogue Act Classification. Proceedings of the 23th International Conference on Computational Linguistics (COLING), Beijing, China."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Raux, A., Bohus, D., Langner, B., Black, A.W., and Eskenazi, M. (2006, January 17\u201321). Doing Research on a Deployed Spoken Dialogue System: One Year of Let\u2019s Go! Experience. Proceedings of the 9th Annual Conference of the International Speech Communication Association (INTERSPEECH), Pittsburgh, PA, USA.","DOI":"10.21437\/Interspeech.2006-17"},{"key":"ref_31","unstructured":"Chorianopoulou, A., Palogiannidi, E., Iosif, E., Koutsakis, P., Georgiladakis, S., Trancoso, I., Batista, F., Moniz, H., Ribeiro, E., and Abad, A. (2019, March 03). Available online: https:\/\/sites.google.com\/site\/spedialproject\/risks-1."},{"key":"ref_32","unstructured":"Alc\u00e1cer, N., Bened\u00ed, J.M., Blat, F., Granell, R., Mart\u00ednez, C.D., and Torres, F. (2005, January 17\u201319). Acquisition and Labelling of a Spontaneous Speech Dialogue Corpus. Proceedings of the 10th International Conference Speech and Computer (SPECOM), Patras, Greece."},{"key":"ref_33","unstructured":"Mart\u00ednez-Hinarejos, C.D., Sanchis, E., Garc\u00eda-Granada, F., and Aibar, P. (2002, January 29\u201331). A Labelling Proposal to Annotate Dialogues. Proceedings of the Third International Conference on Language Resources and Evaluation (LREC), Las Palmas, Spain."},{"key":"ref_34","unstructured":"Jekat, S., Klein, A., Maier, E., Maleck, I., Mast, M., and Quantz, J.J. (1995). Dialogue Acts in VERBMOBIL, DFKI. Technical Report."},{"key":"ref_35","unstructured":"Alexandersson, J., Buschbeck-Wolf, B., Fujinami, T., Kipp, M., Koch, S., Maier, E., Reithinger, N., Schmitz, B., and Siegel, M. (1998). Dialogue Acts in VERBMOBIL-2, DFKI. [2nd ed.]. Technical Report."},{"key":"ref_36","unstructured":"(2019, March 02). Keras: The Python Deep Learning Library. Available online: https:\/\/keras.io\/."},{"key":"ref_37","unstructured":"(2019, March 02). TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. Available online: https:\/\/www.tensorflow.org\/."},{"key":"ref_38","unstructured":"Kingma, D.P., and Ba, J. (2015, January 7\u20139). Adam: A Method for Stochastic Optimization. Proceedings of the 3rd International Conference on Learning Representations (ICLR), San Diego, CA, USA."},{"key":"ref_39","unstructured":"Sorower, M.S. (2010). A Literature Survey on Algorithms for Multi-Label Learning, Oregon State University. Technical Report."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"992","DOI":"10.1016\/j.specom.2008.05.011","article-title":"Statistical Framework for a Spanish Spoken Dialogue Corpus","volume":"50","author":"Granell","year":"2008","journal-title":"Speech Commun."},{"key":"ref_41","unstructured":"(2019, March 02). Spanish Billion Words Corpus and Embeddings. Available online: http:\/\/crscardellino.me\/SBWCE\/."},{"key":"ref_42","unstructured":"(2019, March 02). GermanWordEmbeddings. Available online: https:\/\/github.com\/devmount\/GermanWordEmbeddings."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Ribeiro, E., Ribeiro, R., and de Matos, D.M. (2019). Hierarchical Multi-Label Dialog Act Recognition on Spanish Data. Linguam\u00e1tica, 11, under review.","DOI":"10.21814\/lm.11.1.278"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Reithinger, N., and Klesen, M. (1997, January 22\u201325). Dialogue Act Classification Using Language Models. Proceedings of the Fifth European Conference on Speech Communication and Technology, Rhodes, Greece.","DOI":"10.21437\/Eurospeech.1997-589"}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/3\/94\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:35:59Z","timestamp":1760186159000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/3\/94"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,3]]},"references-count":44,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["info10030094"],"URL":"https:\/\/doi.org\/10.3390\/info10030094","relation":{},"ISSN":["2078-2489"],"issn-type":[{"type":"electronic","value":"2078-2489"}],"subject":[],"published":{"date-parts":[[2019,3,3]]}}}