Popular GitHub Repositories for Grammatical Error Correction

Distilled variant of Whisper for speech recognition. 6x faster, 50% smaller, within 1% word error rate.

Enhance Tesseract OCR output for scanned PDFs by applying Large Language Model (LLM) corrections.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)

Jenetics - Genetic Algorithm, Genetic Programming, Grammatical Evolution, Evolutionary Algorithm, and Multi-objective Optimization

Evaluate your speech-to-text system with similarity measures such as word error rate (WER)

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

NeuSpell: A Neural Spelling Correction Toolkit

Claude Code dashboard with usage stats, error analysis, and sharable feature

??Woodpecker: Hallucination Correction for Multimodal Large Language Models

A fast, low-resource Natural Language Processing and Text Correction library written in Rust.

Use AI-powered code edits, explanations, code generation, error diagnosis, and chat in Visual Studio Code with the official OpenAI API.

Failure archive for ChatGPT and similar models

NLP in Python with Deep Learning

Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.

Project page of the paper "Learning Multi-Scale Photo Exposure Correction" (CVPR 2021).

? [BMVC 2022] You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction. SOTA for low light enhancement, 0.004 seconds try this for pre-processing.

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

White balance camera-rendered sRGB images (CVPR 2019) [Matlab & Python]