This paper describes the UNITOR system that participated to the itaLIan Speech acT labEliNg task within the context of EvalIta 2018. A Structured Kernel-based Support Vector Machine has been here applied to make the classification of the dialogue turns sensitive to the syntactic and semantic information of each utterance, without relying on any task-specific manual feature engineering. Moreover, a specific Markovian formulation of the SVM is adopted, so that the labeling of each utterance depends on speech acts assigned to the previous turns. The UNITOR system ranked first in the competition, suggesting that the combination of the adopted structured kernel and the Markovian modeling is beneficial.
Croce, D., Basili, R. (2018). A markovian kernel-based approach for Italian speech acT labEliNg. In CEUR Workshop Proceedings. CEUR-WS.
A markovian kernel-based approach for Italian speech acT labEliNg
Croce, Danilo;Basili, Roberto
2018-01-01
Abstract
This paper describes the UNITOR system that participated to the itaLIan Speech acT labEliNg task within the context of EvalIta 2018. A Structured Kernel-based Support Vector Machine has been here applied to make the classification of the dialogue turns sensitive to the syntactic and semantic information of each utterance, without relying on any task-specific manual feature engineering. Moreover, a specific Markovian formulation of the SVM is adopted, so that the labeling of each utterance depends on speech acts assigned to the previous turns. The UNITOR system ranked first in the competition, suggesting that the combination of the adopted structured kernel and the Markovian modeling is beneficial.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
