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This study presents a method that assesses ESL learners ’ vocabulary usage to improve an automated scoring system of spontaneous speech responses by non-native English speakers. Focusing on vocabulary sophistication, we estimate the difficulty of each word in the vocabulary based on its frequency in a reference corpus and assess the mean difficulty level of the vocabulary usage across the responses (vocabulary profile). Three different classes of features were generated based on the words in a spoken response: coverage-related, average word rank and the average word frequency and the extent to which they influence human-assigned language proficiency scores was studied. Among these three types of features, the average word frequency showed the most predictive power. We then explored the impact of vocabulary profile features in an automated speech scoring context, with particular focus on the impact of two factors: genre of reference corpora and the characteristics of item-types. The contribution of the current study lies in the use of vocabulary profile as a measure of lexical sophistication for spoken language assessment, an aspect heretofore unexplored in the context of automated speech scoring. 1
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