Building a Smart Interactive Kiosk for Tourist Assistance

Authors

  • Hanane Amessafi Laboratory of electrical engineering and energetic systems Faculty of Sciences,Kenitra, Ibn Tofail University, Kenitra, Morocco
  • Reda Jourani Information Systems Engineering Group Polydisciplinary Faculty of Tétouan, AbdelMalek Essaâdi University, Tétouan, Morocco
  • Adil Echchelh Laboratory of electrical engineering and energetic systems Faculty of Sciences,Kenitra, Ibn Tofail University, Kenitra, Morocco
  • Houssain Oulad Yakhlef Modelling and information theory Group Polydisciplinary Faculty of Tétouan, AbdelMalek Essaâdi University, Tétouan, Morocco

DOI:

https://doi.org/10.14738/tmlai.54.3326

Keywords:

Automatic Language Recognition, Automatic Speech Recognition, keyword extraction, question answering, Gaussian Mixture models, tourism

Abstract

The tourism sector in morocco is increasing rapidly, is well developed, with a strong tourist industry focused on the country's coast, culture, and history. Morocco is the most politically stable countrie in North Africa, which has allowed tourism to develop. There are some tourist attractions spread over a wide geographical area, which are only visited by a few people at specific times of the year. Additionally, having human tourist guides everywhere and speaking different languages is unfeasible. This work deals with the build of a smart interactive kiosk for tourist assistance. In order to do this, it is necessary to start with an Automatic Language Recognition to recognize the language used by the tourist, then extracting keywords from what the tourist said by using Automatic Speech Recognition techniques among others, and finally the system analyses and ansers to the tourist query by suggesting a set of related informations.

 

 

References

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Journal articles

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Published

2017-09-01

How to Cite

Amessafi, H., Jourani, R., Echchelh, A., & Yakhlef, H. O. (2017). Building a Smart Interactive Kiosk for Tourist Assistance. Transactions on Machine Learning and Artificial Intelligence, 5(4). https://doi.org/10.14738/tmlai.54.3326

Issue

Section

Special Issue : 1st International Conference on Affective computing, Machine Learning and Intelligent Systems