Data augmentation is an important method for evaluating the robustness of and enhancing diversity training data natural language processing (NLP) models. In this paper, we present NL-Augmenter, a new participatory Python-based (NL) framework which supports creation transformations (modifications to data) filters (data splits according specific features). We describe initial set 117 23 variety N...
