{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:55:20Z","timestamp":1742946920944,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319993430"},{"type":"electronic","value":"9783319993447"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-99344-7_9","type":"book-chapter","created":{"date-parts":[[2018,8,28]],"date-time":"2018-08-28T02:45:48Z","timestamp":1535424348000},"page":"93-103","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Study on Dialog Act Recognition Using Character-Level Tokenization"],"prefix":"10.1007","author":[{"given":"Eug\u00e9nio","family":"Ribeiro","sequence":"first","affiliation":[]},{"given":"Ricardo","family":"Ribeiro","sequence":"additional","affiliation":[]},{"given":"David Martins","family":"de Matos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,8,29]]},"reference":[{"key":"9_CR1","unstructured":"Abadi, M., et al.: TensorFlow: large-scale machine learning on heterogeneous systems (2015). https:\/\/www.tensorflow.org\/"},{"key":"9_CR2","unstructured":"Alc\u00e1cer, N., Bened\u00ed, J.M., Blat, F., Granell, R., Mart\u00ednez, C.D., Torres, F.: Acquisition and labelling of a spontaneous speech dialogue corpus. In: SPECOM, pp. 583\u2013586 (2005)"},{"key":"9_CR3","unstructured":"Bened\u00ed, J.M., Lleida, E., Varona, A., Castro, M.J., Galiano, I., Justo, R., de Letona, I.L., Miguel, A.: Design and acquisition of a telephone spontaneous speech dialogue corpus in Spanish: DIHANA. In: LREC, pp. 1636\u20131639 (2006)"},{"key":"9_CR4","unstructured":"Cardellino, C.: Spanish billion words corpus and embeddings (2016). http:\/\/crscardellino.me\/SBWCE\/"},{"key":"9_CR5","unstructured":"Chollet, F., et al.: Keras: the python deep learning library (2015). https:\/\/keras.io\/"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Gamb\u00e4ck, B., Olsson, F., T\u00e4ckstr\u00f6m, O.: Active learning for dialogue act classification. In: INTERSPEECH, pp. 1329\u20131332 (2011)","DOI":"10.21437\/Interspeech.2011-441"},{"key":"9_CR7","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1613\/jair.4992","volume":"57","author":"Y Goldberg","year":"2016","unstructured":"Goldberg, Y.: A primer on neural network models for natural language processing. J. Artif. Intell. Res. 57, 345\u2013420 (2016)","journal-title":"J. Artif. Intell. Res."},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Jaech, A., Mulcaire, G., Hathi, S., Ostendorf, M., Smith, N.A.: Hierarchical character-word models for language identification. In: International Workshop on Natural Language Processing for Social Media, pp. 84\u201393 (2016)","DOI":"10.18653\/v1\/W16-6212"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Ji, Y., Haffari, G., Eisenstein, J.: A latent variable recurrent neural network for discourse relation language models. In: NAACL-HLT, pp. 332\u2013342 (2016)","DOI":"10.18653\/v1\/N16-1037"},{"key":"9_CR10","unstructured":"Jurafsky, D., Shriberg, E., Biasca, D.: Switchboard SWBD-DAMSL Shallow-Discourse-Function Annotation Coders Manual. Tech. Rep. Draft 13, University of Colorado, Institute of Cognitive Science (1997)"},{"key":"9_CR11","unstructured":"Kalchbrenner, N., Blunsom, P.: Recurrent convolutional neural networks for discourse compositionality. In: Workshop on Continuous Vector Space Models and their Compositionality, pp. 119\u2013126 (2013)"},{"key":"9_CR12","unstructured":"Khanpour, H., Guntakandla, N., Nielsen, R.: Dialogue act classification in domain-independent conversations using a deep recurrent neural network. In: COLING, pp. 2012\u20132021 (2016)"},{"issue":"2","key":"9_CR13","first-page":"227","volume":"29","author":"P Kr\u00e1l","year":"2010","unstructured":"Kr\u00e1l, P., Cerisara, C.: Dialogue act recognition approaches. Comput. Inform. 29(2), 227\u2013250 (2010)","journal-title":"Comput. Inform."},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Lee, J.Y., Dernoncourt, F.: Sequential short-text classification with recurrent and convolutional neural networks. In: NAACL-HLT, pp. 515\u2013520 (2016)","DOI":"10.18653\/v1\/N16-1062"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Liu, Y., Han, K., Tan, Z., Lei, Y.: Using context information for dialog act classification in DNN framework. In: EMNLP, pp. 2160\u20132168 (2017)","DOI":"10.18653\/v1\/D17-1231"},{"issue":"4","key":"9_CR16","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1162\/COLI_a_00239","volume":"41","author":"CD Manning","year":"2015","unstructured":"Manning, C.D.: Computational linguistics and deep learning. Comput. Linguist. 41(4), 701\u2013707 (2015)","journal-title":"Comput. Linguist."},{"issue":"11\u201312","key":"9_CR17","doi-asserted-by":"publisher","first-page":"992","DOI":"10.1016\/j.specom.2008.05.011","volume":"50","author":"CD Mart\u00ednez-Hinarejos","year":"2008","unstructured":"Mart\u00ednez-Hinarejos, C.D., Bened\u00ed, J.M., Granell, R.: Statistical framework for a Spanish spoken dialogue corpus. Speech Commun. 50(11\u201312), 992\u20131008 (2008)","journal-title":"Speech Commun."},{"key":"9_CR18","first-page":"1566","volume":"5","author":"CD Mart\u00ednez-Hinarejos","year":"2002","unstructured":"Mart\u00ednez-Hinarejos, C.D., Sanchis, E., Garc\u00eda-Granada, F., Aibar, P.: A labelling proposal to annotate dialogues. LREC 5, 1566\u20131582 (2002)","journal-title":"LREC"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Mikolov, T., Karafit, M., Burget, L., Cernock, J., Khudanpur, S.: Recurrent neural network based language model. In: INTERSPEECH, pp. 1045\u20131048 (2010)","DOI":"10.21437\/Interspeech.2010-343"},{"key":"9_CR20","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: NIPS, pp. 3111\u20133119 (2013)"},{"key":"9_CR21","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: GloVe: global vectors for word representation. In: EMNLP, pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"9_CR22","unstructured":"Ribeiro, E., Ribeiro, R., de Matos, D.M.: The influence of context on dialogue act recognition. CoRR abs\/1506.00839 (2015). http:\/\/arxiv.org\/abs\/1506.00839"},{"key":"9_CR23","unstructured":"Santos, C.D., Zadrozny, B.: Learning character-level representations for part-of-speech tagging. In: ICML, pp. 1818\u20131826 (2014)"},{"key":"9_CR24","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139173438","volume-title":"Speech Acts: An Essay in the Philosophy of Language","author":"JR Searle","year":"1969","unstructured":"Searle, J.R.: Speech Acts: An Essay in the Philosophy of Language. Cambridge University Press, Cambridge, London (1969)"},{"issue":"3","key":"9_CR25","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1162\/089120100561737","volume":"26","author":"A Stolcke","year":"2000","unstructured":"Stolcke, A., Coccaro, N., Bates, R., Taylor, P., Van Ess-Dykema, C., Ries, K., Shriberg, E., Jurafsky, D., Martin, R., Meteer, M.: Dialogue act modeling for automatic tagging and recognition of conversational speech. Comput. Linguist. 26(3), 339\u2013373 (2000)","journal-title":"Comput. Linguist."},{"key":"9_CR26","unstructured":"Tamarit, V., Mart\u00ednez-Hinarejos, C.D.: Dialog act labeling in the DIHANA corpus using prosody information. In: V Jornadas en Tecnolog\u00eda del Habla, pp. 183\u2013186 (2008)"},{"key":"9_CR27","first-page":"649","volume":"1","author":"X Zhang","year":"2015","unstructured":"Zhang, X., Zhao, J., LeCun, Y.: Character-level convolutional networks for text classification. NIPS 1, 649\u2013657 (2015)","journal-title":"NIPS"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence: Methodology, Systems, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-99344-7_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T16:26:00Z","timestamp":1709828760000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-99344-7_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319993430","9783319993447"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-99344-7_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"29 August 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIMSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence: Methodology, Systems, and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Varna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bulgaria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aimsa2018a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.aimsaconference.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"22","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2,2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}