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A large number of computational language learners have been proposed for modelling the process of child language acquisition. Comparing them, however, can be difficult due to the different assumptions that they make, the diverse test results presented, and the different linguistic behaviours investigated. This paper introduces a toolkit that allows different language learners to be trained, tested and analysed under standardised conditions. The results can be easily compared with one another and with typical child language development to highlight the relative advantages and disadvantages of learners.

A collaborative tool for the computational modelling of child language acquisition