This study introduces and evaluates a computerized approach to measuring Japanese L2 oral proficiency. We present a testing and scoring method that uses a type of structured speech called elicited imitation (EI) to evaluate accuracy of speech productions. Several types of language resources and toolkits are required to develop, administer, and score responses to this test. First, we present a corpus-based test item creation method to produce EI items with targeted linguistic features in a principled and efficient manner. Second, we sketch how we are able to bootstrap a small learner speech corpus to generate a significantly large corpus of training data for language model construction. Lastly, we show how newly created test items effectively classify learners according to their L2 speaking capability and illustrate how our scoring method computes a metric for language proficiency that correlates well with more traditional human scoring methods.