An empirical assessment of deep learning approaches to task-oriented dialog management Articles uri icon

publication date

  • June 2021

start page

  • 327

end page

  • 339


  • 439

International Standard Serial Number (ISSN)

  • 0925-2312

Electronic International Standard Serial Number (EISSN)

  • 1872-8286


  • Deep learning is providing very positive results in areas related to conversational interfaces, such as speech recognition, but its potential benefit for dialog management has still not been fully studied. In this paper, we perform an assessment of different configurations for deep-learned dialog management with three dialog corpora from different application domains and varying in size, dimensionality and possible system responses. Our results have allowed us to identify several aspects that can have an impact on accuracy, including the approaches used for feature extraction, input representation, context consideration and the hyper-parameters of the deep neural networks employed.


  • Robotics and Industrial Informatics


  • conversational interfaces; deep learning; dialog management; spoken interaction; statistical approaches