Automated semantic grammar generation in dialogue-based task-oriented systems
Typ
Examensarbete för masterexamen
Program
Complex adaptive systems (MPCAS), MSc
Publicerad
2021
Författare
Triantafyllou, Georgios
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Dialogue-base task-oriented systems are conversational systems that can complete tasks and answer questions.
A semantic grammar can be helpful for user input recognition in such systems. Manually creating semantic
grammars can be cumbersome for a developer and delay the deployment of the system, thus it would be of great
assistance to automate the process. The topic of automated semantic grammar generation has not been deeply
explored and current approaches in this field are either semi-automated or lack interpretability and robustness.
In this thesis, the prospect of developing a completely automated semantic grammar generation method was
investigated. An additional aim was to create a method that could be employed in different domains without
needing any additional modifications. We propose a novel method that utilizes syntactic and relation analysis
to infer the semantics of a user input. The method developed is a hybrid approach that comprises statistical
methods for the syntactic analysis and a rule-based model for the semantics. The results show that the method
is able to generate a fairly accurate and precise semantic grammar. It is also observed that the method is not
able to fully analyze all possible pattern cases. Furthermore, the relation analysis has proved to be helpful on
finding semantic synonymity amongst different user input patterns. It is plausible to completely automate the
creation of a semantic grammar and our findings suggest that hybrid approaches can preform well in this task.
Nevertheless, further adjustments should be made in the rule-based model to provide a universal coverage of
pattern cases
Beskrivning
Ämne/nyckelord
Semantic grammar , conversational systems , syntactic analysis , semantic analysis , information extraction