Exploiting unlabeled utterances for spoken language understanding

摘要

A system and method for exploiting unlabeled utterances in the augmentation of a classifier model is disclosed. In one embodiment, a classifier is initially trained using a labeled set of utterances. Another set of utterances is then selected from an available set of unlabeled utterances. In one embodiment, this selection process can be based on a confidence score threshold. The trained classifier is then augmented using the selected set of unlabeled utterances.