Abstract/Summary

Purpose: Connected speech analysis has been effectively utilized for the diagnosis and disease monitoring of individuals with Alzheimer’s Disease (AD). Existing research has been conducted mostly in monolingual English speakers with a noticeable lack of evidence from bilinguals and non-English speakers, particularly in non-European languages. Using a case study approach, we characterized connected speech profiles of two Bengali-English bilingual speakers with AD to: determine the universal features of language impairments in both languages, identify language-specific differences between the languages, and explore language impairment characteristics of the participants with AD in relation to their bilingual language experience. Method: Participants included two Bengali-English bilingual speakers with AD and a group of age-, gender-, education- and language-matched neurologically healthy controls. Connected speech samples were collected in L1 (Bengali) and L2 (English) using a novel storytelling task (i.e., “Frog, where are you?”). These samples were analyzed using an augmented Quantitative Production Analysis and Correct Information Unit analyses for productivity, fluency, syntactic and morpho-syntactic features, lexical and semantic characteristics. Results: Irrespective of the language, AD impacted speech productivity (speech rate and fluency) and semantic characteristics in both languages. Unique language-specific differences were noted on syntactic measures (reduced sentence length in Bengali), lexical distribution (fewer pronouns and absence of reduplication in Bengali) and inflectional properties (no difficulties with noun or verb inflections in Bengali). Among the two participants with AD, the individual who showed lower proficiency and usage in L2 (English) demonstrated reduced syntactic complexity and morpho-syntactic richness in English. Conclusion: Evidence from these case studies suggest that language impairment features in AD are not universal across languages, particularly in comparison to impairments typically associated with language breakdowns in English. This study underscores the importance of establishing connected speech profiles in AD for non-English speaking populations, especially for structurally different languages. This would in turn lead to the development of language-specific markers that can facilitate early detection of language deterioration and aid in improving diagnosis of AD in individuals belonging to underserved linguistically diverse populations.