An ontology-driven semantic speech recognition system for security tasks

One of the goals of speech recognition security (SRS) systems could be to extract the subject of the discourse in order to detect possible risks. Thus, the development of appropriated Speech Semantic Recognition systems is one of the challenges the scientific community has. Our system is an Information Retrieval system that provides information about the contents of audio in Basque, Spanish, and French. Since the resources available for Basque in general, and for this task in particular, were very few, data optimization methodologies had to be applied in various phases of the development. Moreover, the agglutinative nature of Basque required the use of morphemes and other sub-word units. Additionally, some keyword spotting and semantic methods have been also applied in the system in order to retrieve information properly. In most of the cases, the methods employed during this project could suit the requirements of many under-resourced languages, and one of these techniques could be the ontology-based approach. This paper presents the system in general for Basque and emphasizes the techniques employed in order to enhance the system using a semantic ontology.