Exploring Measures of "Readability" for Spoken Language: Analyzing linguistic features of subtitles to identify age-specific TV programs

We investigate whether measures of readability can be used to identify age-specific TV programs. Based on a corpus of BBC TV subtitles, we employ a range of linguistic readability features motivated by Second Language Acquisition and Psycholinguistics research. Our hypothesis that such readability features can successfully distinguish between spoken language targeting different age groups is fully confirmed. The classifiers we trained on the basis of these readability features achieve a classification accuracy of 95.9%. Investigating several feature subsets, we show that the authentic material targeting specific age groups exhibits a broad range of linguistics and psycholinguistic characteristics that are indicative of the complexity of the language used.