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Link to original content: https://doi.org/10.1007/978-3-031-40725-3_43
Statistical Dialog Tracking and Management for Task-Oriented Conversational Systems | SpringerLink
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Statistical Dialog Tracking and Management for Task-Oriented Conversational Systems

  • Conference paper
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Hybrid Artificial Intelligent Systems (HAIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14001))

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Abstract

Conversational interfaces offer users a natural way to interact with a range of applications and devices. Human-machine interaction using these systems involves different components that mimic the mechanisms used by humans when using language and speech interaction. In this paper, we are interested in automatically developing the dialog state tracking component for task-oriented conversational systems to automatically decide the best system response from a set of predefined responses. To do this, we have evaluated several statistical methodologies to develop this component for a conversational system that provides technical program information during conferences. Gradient boosting trees have been selected as the best performing method for this specific domain.

The research leading to these results has received funding from “CONVERSA: Effective and efficient resources and models for transformative conversational AI in Spanish and co-official languages” project with reference TED2021-132470B-I00, funded by MCIN/AEI/10.13039/501100011033 and by the European Union “NextGenerationEU”/PRTR”. Work also partially supported from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 823907 (MENHIR project: https://menhir-project.eu) and the GOMINOLA project (PID2020-118112RB-C21 and PID2020-118112RB-C22, funded by MCIN/AEI/10.13039/501100011033).

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Notes

  1. 1.

    https://rasa.com/.

References

  1. Batish, R.: Voicebot and Chatbot Design: Flexible Conversational Interfaces with Amazon Alexa, Google Home, and Facebook Messenger. Packt Publishing Ltd. (2018)

    Google Scholar 

  2. Bhatia, P., Gavaldà, M., Einolghozati, A.: soc2seq: social embedding meets conversation model. arXiv:1702.05512 (2017)

  3. Cuayáhuitl, H., et al.: Ensemble-based deep reinforcement learning for chatbots. Neurocomputing 366, 118–130 (2019). https://doi.org/10.1016/j.neucom.2019.08.007

    Article  Google Scholar 

  4. Gao, C., Lei, W., He, X., de Rijke, M., Chua, T.S.: Advances and challenges in conversational recommender systems: a survey. AI Open 2, 100–126 (2021). https://doi.org/10.1016/j.aiopen.2021.06.002

    Article  Google Scholar 

  5. Janarthanam, S.: Hands-On Chatbots and Conversational UI Development: Build Chatbots and Voice User Interfaces with Chatfuel, Dialogflow, Microsoft Bot Framework, Twilio, and Alexa Skills. Packt Publishing Ltd. (2017)

    Google Scholar 

  6. Lee, H., Lee, J., Kim, T.Y.: SUMBT: slot-utterance matching for universal and scalable belief tracking. In: Proceedings of ACL 2019, Florence, Italy, pp. 5478–5483 (2019). https://doi.org/10.18653/v1/P19-1546

  7. Li, B., Zhan, Y., Wei, Z., Huang, S., Sun, L.: Improved non-autoregressive dialog state tracking model. In: Proceedings of ICCIR 2021, Qingdao, China, pp. 199–203 (2021). https://doi.org/10.48550/arXiv.2002.08024

  8. Li, C., Zhang, X., Chrysostomou, D., Yang, H.: ToD4IR: a humanised task-oriented dialogue system for industrial robots. IEEE Access 10, 91631–91649 (2022). https://doi.org/10.1109/ACCESS.2022.3202554

    Article  Google Scholar 

  9. Lison, P., Kennington, C.: OpenDial: a toolkit for developing spoken dialogue systems with probabilistic rules. In: Proceedings of ACL 2016, Berlin, Germany, pp. 67–72 (2016). https://doi.org/10.18653/v1/P16-4012

  10. McTear, M.: Conversational AI. Dialogue Systems, Conversational Agents, and Chatbots. Morgan and Claypool Publishers (2020)

    Google Scholar 

  11. McTear, M., Callejas, Z., Griol, D.: The Conversational Interface: Talking to Smart Devices. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-319-32967-3

    Book  Google Scholar 

  12. Wen, T.H., et al.: A network-based end-to-end trainable task-oriented dialogue system. In: Proceedings of EACL 2017, Valencia, Spain, pp. 438–449 (2017). https://doi.org/10.48550/arXiv.1604.04562

  13. Young, T., Xing, F., Pandelea, V., Ni, J., Cambria, E.: Fusing task-oriented and open-domain dialogues in conversational agents. In: Proceedings of AAAI 2021 (2021). https://doi.org/10.48550/arXiv.2109.04137

  14. Zhao, C., et al.: What do others think?: task-oriented conversational modeling with subjective knowledge. arXiv:2305.12091 (2023)

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Author information

Authors and Affiliations

  1. CITIC-UGR, Department Software Engineering, University of Granada, Periodista Daniel Saucedo Aranda sn, 18071, Granada, Spain

    David Griol & Zoraida Callejas

Authors
  1. David Griol
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  2. Zoraida Callejas
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Corresponding author

Correspondence to David Griol .

Editor information

Editors and Affiliations

  1. University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of Leon, León, Spain

    Hilde Pérez García

  3. University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  4. Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. University of Burgos, Burgos, Spain

    Álvaro Herrero

  7. University of A Coruña, Ferrol - Coruña, Spain

    José Luis Calvo Rolle

  8. University of A Coruña, Ferrol - Coruña, Spain

    Héctor Quintián

  9. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Griol, D., Callejas, Z. (2023). Statistical Dialog Tracking and Management for Task-Oriented Conversational Systems. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_43

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  • DOI: https://doi.org/10.1007/978-3-031-40725-3_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-40724-6

  • Online ISBN: 978-3-031-40725-3

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