Data Augmentation by Backtranslation (DAB) ヽ( •_-)ᕗ
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Updated
Jun 20, 2022 - Jupyter Notebook
Data Augmentation by Backtranslation (DAB) ヽ( •_-)ᕗ
Cross-lingual Language Model (XLM) pretraining and Model-Agnostic Meta-Learning (MAML) for fast adaptation of deep networks
Bangla Text Augmentation
Low resource machine translation using Transformers and Iterative Back translation
Implementing 5 Different Approaches To Augmenting Data For Natural Language Processing Tasks.
Source code and data for paper ``Unsupervised Dual Paraphrasing for Two-stage Semantic Parsing" in ACL 2020.
An attempt to make Back-Translation differentiable, using probability weighted embeddings for predicted translations in the nucleus of the predicted distribution over target language sentences.
A PyTorch implementation of a transformer network trained using back-translation
Low resource language machine translation(az,be,tr -> en).
This repo offers a Python script using NLPAug library & RTT to augment text datasets. It processes TXT files in "data/" folder, translating text and creating augmented versions. Augmented data enhances NLP tasks like chatbot training & text classification. Includes overview of techniques, applications & implementation.
Common approaches to text augmentation, from random text-editing perturbations, back translation, to model-based transformations.
Code associated with the "Enhanced Cognitive Distortions Detection and Classification through Data Augmentation Techniques" paper
A text generation library to paraphrase image captions using back translations or transfer learning.
BackTranslation Experiment
Noise Identification, Noise reduction, and Sentiment Analysis on Bangla Noisy Texts
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