About

You can read these blog posts to get an overview of the approaches.

Benchmarks

No evaluation results yet. Help compare methods by submit evaluation metrics.

Greatest papers with code

Multilingual Augmenter: The Model Chooses

19 Feb 2021makcedward/nlpaug

Natural Language Processing (NLP) relies heavily on training data.

TEXT AUGMENTATION

Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations

NAACL 2018 makcedward/nlpaug

We stochastically replace words with other words that are predicted by a bi-directional language model at the word positions.

CLASSIFICATION LANGUAGE MODELLING TEXT AUGMENTATION TEXT CLASSIFICATION

Learning to Compose Domain-Specific Transformations for Data Augmentation

NeurIPS 2017 HazyResearch/tanda

Data augmentation is a ubiquitous technique for increasing the size of labeled training sets by leveraging task-specific data transformations that preserve class labels.

IMAGE AUGMENTATION RELATION EXTRACTION TEXT AUGMENTATION

Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding

COLING 2018 AtmaHou/Seq2SeqDataAugmentationForLU

In this paper, we study the problem of data augmentation for language understanding in task-oriented dialogue system.

TEXT AUGMENTATION

Text Augmentation for Language Models in High Error Recognition Scenario

11 Nov 2020BUTSpeechFIT/BrnoLM

We examine the effect of data augmentation for training of language models for speech recognition.

SPEECH RECOGNITION TEXT AUGMENTATION

Text Data Augmentation Made Simple By Leveraging NLP Cloud APIs

5 Dec 2018ClaudeCoulombe/TextDataAugmentation

In practice, it is common to find oneself with far too little text data to train a deep neural network.

TEXT AUGMENTATION