Ontology-based framework for a multi-domain spoken dialogue system

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A3639L9KE" target="_blank" >RIV/00216208:11320/25:3639L9KE - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049565494&doi=10.1007%2fs12652-017-0625-y&partnerID=40&md5=482bbdfda1342acd0c88aff9900af098" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049565494&doi=10.1007%2fs12652-017-0625-y&partnerID=40&md5=482bbdfda1342acd0c88aff9900af098</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s12652-017-0625-y" target="_blank" >10.1007/s12652-017-0625-y</a>

Result language

angličtina

Original language name

Ontology-based framework for a multi-domain spoken dialogue system

Original language description

Multi-domain spoken dialogue is a challenging field where the objective of the most proposed ideas is to mimic the human–human dialogue. This paper proposes to tackle the domain selection problem in the context of multi-domain spoken dialogue as a set theory problem to resolve. First, we built each dialogue domain as an ontology following an architecture with some rules to respect. Second, each ontology is considered as a set and its concepts are the elements. Third, an ontology-based classifier is used to map the user sentence into a set of ontologies concepts and to generate an intersection between these concepts. Finally, a new turn analysis and domain selection algorithm is proposed to infer the intended domain from the user sentence using the intersection set and three techniques, namely Domain Rewards, Dominant Concept, and Current Domain. To evaluate the proposed approach, a corpus of 120 simulated dialogues was built to cover four application domains. In our experiment, the assessment of the system is performed by considering all possibilities of a natural verbal interaction where a changing of semantic context occurs during the dialogue. The obtained results show that the system accuracy reaches a satisfactory performance of 83.13% while the average number of turns by dialogue is 6.79. © Springer-Verlag GmbH Germany, part of Springer Nature 2017.

Czech name

—

Czech description

—

Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

—

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Ambient Intelligence and Humanized Computing

ISSN

1868-5137

e-ISSN

—

Volume of the periodical

15

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

23

Pages from-to

1543-1565

UT code for WoS article

—

EID of the result in the Scopus database

2-s2.0-85049565494