Popular GitHub Repositories for Linguistic Steganography

Code for ICLR 2020 paper "VL-BERT: Pre-training of Generic Visual-Linguistic Representations".

INTERSPEECH 2023-2024 Papers: A complete collection of influential and exciting research papers from the INTERSPEECH 2023-24 conference. Explore the latest advances in speech and language processing. Code included. Star the repository to support the advancement of speech technology!

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

Exploring attention weights in transformer-based models with linguistic knowledge.

Code for "Aligning Linguistic Words and Visual Semantic Units for Image Captioning", ACM MM 2019

[BEA @ ACL 2023] General-purpose tool for linguistic features extraction; Tested on readability assessment, essay scoring, fake news detection, hate speech detection, etc.

[EMNLP 2021] LingFeat - A Comprehensive Linguistic Features Extraction ToolKit for Readability Assessment

? ChatLog: Recording and Analysing ChatGPT Across Time

LLM steganography with minimum-entropy coupling - Hiding encrypted messages in natural language.

Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)

Implementation of "Invisible Steganography via Generative Adversarial Networks" (https://arxiv.org/abs/1807.08571)

core code for High-Capacity Convolutional Video Steganography with Temporal Residual Modeling

Text style transfer benchmark

A comprehensive tool for linguistic analysis of communities

Python library for extracting quantitative, reproducible metrics of multi-level alignment between speakers in naturalistic language corpora.

Scripts to generate the CoDraw and i-CLEVR datasets used for the GeNeVA task proposed in our ICCV 2019 paper "Tell, Draw, and Repeat: Generating and modifying images based on continual linguistic instruction"

Novoic's linguistic feature extraction library

Modified version of RusStress (https://github.com/MashaPo/russtress) — python package for placing stress in Russian text using RNN (BiLSTM) and the "Grammatical Dictionary" by A. A. Zaliznyak (from http://odict.ru/).

Pytorch Implementation of the paper: Multi-Image Steganography Using Deep Neural Networks by Abhishek et. al.

Linguistica 5: Unsupervised Learning of Linguistic Structure