engleski

Automatic Text Analysis in Language Assessment: Developing a MultiDis Web Application

Language sample analysis provides rich information about the language abilities in the written or spoken text produced by a speaker in response to a language task. Language sample analysis is generally used to assess the abilities of children during language acquisition, but also the abilities of adult speakers across the lifespan. Its wide range of uses also allows for the assessment of language abilities in educational contexts such as second language acquisition or fluency, the abilities of bilingual speakers in general, and it is also used for diagnosis in speech and language pathology. Various computer programs have been developed to assist in the language sample analysis. However, these programs have been developed mainly for English and are often not fully open-access or do not provide data on population metrics, history of data uploaded by a user, and/or improvements in basic language measures. The time needed for transcription and the linguistic knowledge required for manual analysis are considered to be the main obstacles to its implementation The goal of this paper is to present a web-based application MultiDis intended for the analysis of language samples at the microstructural text level in Croatian. The application is still under development, but the current version fulfils its main purpose – it enables the (semi-)automatic calculation of measures reflecting language productivity, lexical diversity, syntactic complexity, and discourse cohesion in spoken language, and provides users with socio-demographic and linguistic metadata as well as the history of uploaded transcripts. We will present the challenges we have faced in developing the application (e.g., annotation system, text standardisation), future improvements we plan to make to the application (e.g., syntactic parsing, speech-to-text, multilingual analysis), and the possibilities of its use in the wider scientific and professional community.

Automatic Text Analysis ; Language Assessement ; Language Measures ; Natural Language Processing ; Web Application

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