Augmenty: A Python Library for Structured Text Augmentation
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Abstract (arXiv)
Augmnety is a Python library for structured text augmentation. It is built on top of spaCy and allows for augmentation of both the text and its annotations. Augmenty provides a wide range of augmenters which can be combined in a flexible manner to create complex augmentation pipelines. It also includes a set of primitives that can be used to create custom augmenters such as word replacement augmenters. This functionality allows for augmentations within a range of applications such as named entity recognition (NER), part-of-speech tagging, and dependency parsing.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 16 references that are in the map. First posted on arXiv 9 Dec 2023.
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References · 8
- 2019SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognitioncited by 1,355
- 2020Beyond Accuracy: Behavioral Testing of NLP models with CheckListcited by 979
- 2019EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Taskscited by 800
- 2017The Effectiveness of Data Augmentation in Image Classification using Deep Learningcited by 368
- 2021Robustness Gym: Unifying the NLP Evaluation Landscapecited by 107
- 2019Improving short text classification through global augmentation methodscited by 33
- 2023ScandEval: A Benchmark for Scandinavian Natural Language Processingcited by 16
- 2021DaCy: A Unified Framework for Danish NLPcited by 10
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