Signterpreter

American Sign Language (ASL) to Text Converter

Recommendations

Although there is grayscale and gaussian blur, we recommend that you use this application with a wall or greenscreen right behind you. It is not perfect at distinguishing behind hand gestures and different objects in the background.

Packages

You will need to download a few packages with the latest version of pip. By running the following code segment in command prompt, you should be able to run the application perfectly:

1. Latest pip -> pip install --upgrade pip

2. numpy -> pip install numpy

3. string -> pip install strings

4. os-sys -> pip install os-sys

5. opencv -> pip install opencv-python

6. tensorFlow -> i) pip install tensorflow 
                 ii) pip3 install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp34-cp34m-linux_x86_64.whl
7. keras -> pip install keras

8. tkinter -> pip install tk

9. PIL -> pip install Pillow

10. enchant -> pip install pyenchant (Python bindings for the Enchant spellchecking system)

11. hunspell -> pip install cyhunspell (A wrapper on hunspell for use in Python)

What is not Included

We have not attached our training and testing dataset due to the sheer amount of files. To create your own dataset to train and test the model, you will need to run the following applications by opening them or using command prompt:

1. FoldersCreation.py -> python FoldersCreation.py

2. TestingDataCollection.py -> python TestingDataCollection.py

3. TrainingDataCollection.py -> python TrainingDataCollection.py

American Sign Language (ASL) to Text Converter

Related tags

Overview

Signterpreter

Recommendations

Packages

What is not Included

Owner

UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language

Exploring dimension-reduced embeddings

A sample project that exists for PyPUG's "Tutorial on Packaging and Distributing Projects"

Finetune gpt-2 in google colab

Search Git commits in natural language

PhoNLP: A BERT-based multi-task learning toolkit for part-of-speech tagging, named entity recognition and dependency parsing

Estimation of the CEFR complexity score of a given word, sentence or text.

Source code for the paper "TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations"

Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.

The proliferation of disinformation across social media has led the application of deep learning techniques to detect fake news.

This is a simple item2vec implementation using gensim for recbole

PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer

A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

Final Project Bootcamp Zero

Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"

Twitter bot that uses NLP models to summarize news articles referenced in a user's twitter timeline

official ( API ) for the zAmericanEnglish app in [ Google play ] and [ App store ]

Official implementation of Meta-StyleSpeech and StyleSpeech

fastai ulmfit - Pretraining the Language Model, Fine-Tuning and training a Classifier

Transformer Based Korean Sentence Spacing Corrector