DERIVING LOCAL RELATIONAL SURFACE FORMS FROM DEPENDENCY-BASED ENTITY EMBEDDINGS FOR UNSUPERVISED SPOKEN LANGUAGE UNDERSTANDING

ABSTRACT Recent works showed the trend of leveraging web-scaled structured semantic knowledge resources such as Freebase for open domain spoken language understanding (SLU). Knowledge graphs provide sufficient but ambiguous relations for the same entity, which can be used as statistical background knowledge to infer possible relations for interpretation of user utterances. This paper proposes an approach to capture the relational surface forms by mapping dependency-based contexts of entities from the text domain to the spoken domain. Relational surface forms are learned from dependency-based entity embeddings, which encode the contexts of entities from dependency trees in a deep learning model. The derived surface forms carry functional dependency to the entities and convey the explicit expression of relations. The experiments demonstrate the efficiency of leveraging derived relational surface forms as local cues together with prior background knowledge. Index Terms-spoken language understanding (SLU), relation detection, semantic knowledge graph, entity embeddings, spoken dialogue systems (SDS)

Lexical retrieval in bilingual Sinhala-English and monolingual Sinhala healthy speakers and speakers with aphasia

When language breakdown subsequent to neural injury occurs, an apparent disruption of language production skills follow. This is particularly evident in the major grammatical classes of nouns and verbs. This deficit could be selective, effecting either nouns or verbs or both in asymmetrical severity, in selected language modalities or at varied linguistic complexity (i.e. naming vs. connected speech). In bilinguals, these selective disassociation may manifest in equal or varying degrees across the languages known. This is influenced by the differences in the linguistic structure of the bilinguals’ languages. The need for language and culture specific assessment tool and data is therefore critical. This three-phase cross sectional exploratory study aimed to compare word retrieval skills in monolingual and bilingual people with aphasia (PwAs) post stroke. Investigated here are specific language populations of Sri Lanka; Sinhala monolingual (ML) and Sinhala- English bilingual (BL) healthy speakers and PwAs who have not been studied to date. In the first phase, the study adapted test tools and material published in English and develops some other stimuli anew, to gather data from healthy adults. This data was then used as a normative baseline against which 26 PwAs in the said populations were assessed in the second and third phases of the study. The subsequent data compared word production performances between and within the language conditions in the ML and BL groups, across word classes and language tasks. It is anticipated that the findings of this study would contribute towards the cross-linguistic database on aphasia in bilingual speakers and particularly towards developing an evidence-based research and clinical platform for bilingual PwAs in Sri Lanka