Raquel Fernández

Here you can find the supplementary material and the annotated data used in the following paper, which is based on Sarah Hiller's MSc thesis:

Sarah Hiller & Raquel Fernández, A Data-driven Investigation of Corrective Feedback on Subject Omission Errors in First Language Acquisition, in Proceedings of the SIGNLL Conference on Computational Natural Language Learning (CoNLL), 2016. Best Paper Award.

We investigate implicit corrections in the form of contrastive discourse in child-adult interaction, which have been argued to contribute to language learning. In contrast to previous work in psycholinguistics, we adopt a data-driven methodology, using comparably large amounts of data and leveraging computational methods. We conduct a corpus study on the use of parental corrective feedback and show that its presence in child directed speech is associated with a reduction of child subject omission errors in English.