Aportaciones al etiquetado y segmentación automática de diálogos en el corpus DIHANA

El siguiente trabajo estudia varios métodos para el etiquetado automático de segmentos en los sistemas de diálogo hablados. Concretamente, se centra la experimentación en el corpus de diálogo Dihana. El estudio aborda la eficacia de la prosodia (información extraída de la señal, que caracteriza el habla) por sí misma para identificar actos de diálogo y su combinación con las transcripciones de las intervenciones. También se presenta un método de etiquetado basado en la transcripción que utiliza HMMs. Este modelo se presenta en distintas versiones, fruto de realizar distintas asunciones en el desarrollo del planteamiento por máxima verosimilitud. Se presenta también otro método basado en la transcripción que utiliza técnicas de alineamiento típicas de la traducción automática.Tamarit Ballester, V. (2008). Aportaciones al etiquetado y segmentación automática de diálogos en el corpus DIHANA. http://hdl.handle.net/10251/13637Archivo delegad

Improving Unsegmented Dialogue Turns Annotation with N-gram Transducers

PACLIC 23 / City University of Hong Kong / 3-5 December 200

Estimating the number of segments for improving dialogue act labelling

In dialogue systems it is important to label the dialogue turns with dialogue-related meaning. Each turn is usually divided into segments and these segments are labelled with dialogue acts (DAs). A DA is a representation of the functional role of the segment. Each segment is labelled with one DA, representing its role in the ongoing discourse. The sequence of DAs given a dialogue turn is used by the dialogue manager to understand the turn. Probabilistic models that perform DA labelling can be used on segmented or unsegmented turns. The last option is more likely for a practical dialogue system, but it provides poorer results. In that case, a hypothesis for the number of segments can be provided to improve the results. We propose some methods to estimate the probability of the number of segments based on the transcription of the turn. The new labelling model includes the estimation of the probability of the number of segments in the turn. We tested this new approach with two different dialogue corpora: SwitchBoard and Dihana. The results show that this inclusion significantly improves the labelling accuracy. © Copyright Cambridge University Press 2011.Work supported by the EC (FEDER/FSE), the Spanish Government (MEC, MICINN, MITyC, MAEC, "Plan E", under grants MIPRCV "Consolider Ingenio 2010" CSD2007-00018, MITTRAL TIN2009-14633-C03-01, erudito.com TSI-020110-2009-439, FPI fellowship BES-2007-16834), and Generalitat Valenciana (grant Prometeo/2009/014 and grant ACOMP/2010/051).Tamarit Ballester, V.; Martínez-Hinarejos, C.; Benedí Ruiz, JM. (2012). Estimating the number of segments for improving dialogue act labelling. Natural Language Engineering. 18(1):1-19. doi:10.1017/S135132491000032XS119181Dybkjær, L., & Minker, W. (Eds.). (2008). Recent Trends in Discourse and Dialogue. Text, Speech and Language Technology. doi:10.1007/978-1-4020-6821-8Stolcke, A., Ries, K., Coccaro, N., Shriberg, E., Bates, R., Jurafsky, D., … Meteer, M. (2000). Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech. Computational Linguistics, 26(3), 339-373. doi:10.1162/089120100561737Fraser, N. M., & Gilbert, G. N. (1991). Simulating speech systems. Computer Speech & Language, 5(1), 81-99. doi:10.1016/0885-2308(91)90019-mSchatzmann J. , Thomson B. and Young S. 2007. Statistical user simulation with a hidden agenda. In Proceedings of the SIGdial Workshop on Discourse and Dialogue, pp. 273–82.Levin L. , Ries K. , Thymé-Gobbel A. , and Levie A. 1999. Tagging of speech acts and dialogue games in Spanish call home. In Workshop: Towards Standards and Tools for Discourse Tagging, pp. 42–7.Hinarejos, C. D. M., Granell, R., & Benedí, J. M. (2006). Segmented and unsegmented dialogue-act annotation with statistical dialogue models. Proceedings of the COLING/ACL on Main conference poster sessions -. doi:10.3115/1273073.1273146Benedí J. M. , Lleida E. , Varona A. , Castro M. J. , Galiano I. , Justo R. , López de Letona I. , and Miguel A. 2006. Design and acquisition of a telephone spontaneous speech dialogue corpus in Spanish: Dihana. In Fifth International Conference on Language Resources and Evaluation (LREC), pp. 1636–9.Young, S. J. (2000). Probabilistic methods in spoken–dialogue systems. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 358(1769), 1389-1402. doi:10.1098/rsta.2000.0593Martínez-Hinarejos, C.-D., Benedí, J.-M., & Granell, R. (2008). Statistical framework for a Spanish spoken dialogue corpus. Speech Communication, 50(11-12), 992-1008. doi:10.1016/j.specom.2008.05.011Bisani M. and Ney H. 2004. Bootstrap estimates for confidence intervals in asr performance evaluation. In Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on, vol. 1, pp. 1:I–409–12.Garcia, P., & Vidal, E. (1990). Inference of k-testable languages in the strict sense and application to syntactic pattern recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(9), 920-925. doi:10.1109/34.57687Jurafsky D. , Shriberg E. and Biasca D. 1997. Switchboard SWBD-DAMSL shallow discourse function annotation coders manual - draft 13. Technical Report 97-01, University of Colorado Institute of Cognitive Science.Gorin, A. ., Riccardi, G., & Wright, J. . (1997). How may I help you? Speech Communication, 23(1-2), 113-127. doi:10.1016/s0167-6393(97)00040-xWalker, M. A. (2000). An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email. Journal of Artificial Intelligence Research, 12, 387-416. doi:10.1613/jair.713Core M. G. and Allen J. F. 2007. Coding dialogues with the DAMSL annotation scheme. In Fall Symposium on Communicative Action in Humans and Machines. American Association for Artificial Intelligence, pp. 28–35.Fukada T. , Koll D. , Waibel A. and Tanigaki K. 1998. Probabilistic dialogue act extraction for concept based multilingual translation systems. ICSLP 98 2771–4

Bibliografía histórica sobre la ciencia y la técnica en España, 2000

Repertori de bibliografia històrica sobre la ciència i la tècnica a Espanya editada en 2000. // Repertorio de bibliografía histórica sobre la ciencia y la técnica en España editada en 2000

Risk Factors for COVID-19 in Inflammatory Bowel Disease: A National, ENEIDA-Based Case–Control Study (COVID-19-EII)

(1) Scant information is available concerning the characteristics that may favour the acquisition of COVID-19 in patients with inflammatory bowel disease (IBD). Therefore, the aim of this study was to assess these differences between infected and noninfected patients with IBD. (2) This nationwide case-control study evaluated patients with inflammatory bowel disease with COVID-19 (cases) and without COVID-19 (controls) during the period March-July 2020 included in the ENEIDA of GETECCU. (3) A total of 496 cases and 964 controls from 73 Spanish centres were included. No differences were found in the basal characteristics between cases and controls. Cases had higher comorbidity Charlson scores (24% vs. 19%; p = 0.02) and occupational risk (28% vs. 10.5%; p < 0.0001) more frequently than did controls. Lockdown was the only protective measure against COVID-19 (50% vs. 70%; p < 0.0001). No differences were found in the use of systemic steroids, immunosuppressants or biologics between cases and controls. Cases were more often treated with 5-aminosalicylates (42% vs. 34%; p = 0.003). Having a moderate Charlson score (OR: 2.7; 95%CI: 1.3-5.9), occupational risk (OR: 2.9; 95%CI: 1.8-4.4) and the use of 5-aminosalicylates (OR: 1.7; 95%CI: 1.2-2.5) were factors for COVID-19. The strict lockdown was the only protective factor (OR: 0.1; 95%CI: 0.09-0.2). (4) Comorbidities and occupational exposure are the most relevant factors for COVID-19 in patients with IBD. The risk of COVID-19 seems not to be increased by immunosuppressants or biologics, with a potential effect of 5-aminosalicylates, which should be investigated further and interpreted with caution