From Spoken Language to Ontology-Driven Dialogue Management

  • Dmitry Mouromtsev
  • Liubov Kovriguina
  • Yury Emelyanov
  • Dmitry Pavlov
  • Alexander Shipilo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9302)


The paper describes the architecture of the prototype of the spoken dialogue system combining deep natural language processing with an information state dialogue manager. The system assists technical support to the customers of the digital TV provider. Raw data are sent to the natural language processing engine which performs tokenization, morphological and syntactic analysis and anaphora resolution. Multimodal Interface Language (MMIL) is used for the sentence semantic representation. A separate module of the NLP engine converts Shallow MMIL representation into Deep MMIL representation by applying transformation rules to shallow syntactic structures and generating its paraphrases. Deep MMIL representation is the input of the module generating facts for the dialogue manager. Facts are extracted using the domain ontology. A fact itself is an RDF triple containing temporal information wrapped in the move type. Dialogue manager can accept unlimited number of facts and supports mixed initiative.


Spoken dialogue systems Domain ontology development Natural language processing MMIL applications Paraphrase generation Information state approach 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Dmitry Mouromtsev
    • 1
  • Liubov Kovriguina
    • 1
  • Yury Emelyanov
    • 1
  • Dmitry Pavlov
    • 1
  • Alexander Shipilo
    • 2
  1. 1.ISST LaboratoryITMO UniversitySaint-PetersburgRussia
  2. 2.Saint-Petersburg State UniversitySaint-PetersburgRussia

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