Top 1176 natural-language-processing open source projects

Paper list of NLP for recommender systems

Library to scrape and clean web pages to create massive datasets.

R package for Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing Based on the UDPipe Natural Language Processing Toolkit

Browse Covid-19 & SARS-CoV-2 Scientific Papers with Transformers 🦠 📖

This is a JSON driven angular x based dashboard framework that is inspired by JIRA's dashboard implementation and https://github.com/raulgomis/angular-dashboard-framework

A Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia

MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification

Basic Utilities for PyTorch Natural Language Processing (NLP)

《机器翻译：基础与模型》肖桐 朱靖波 著 - Machine Translation: Foundations and Models

Mishkal is an arabic text vocalization software

Python library for Natural Language Preprocessing (NLPre)

Topic Modelling for Humans

📖 A curated list of resources dedicated to Natural Language Processing (NLP)

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

SLING - A natural language frame semantics parser

PyTorch code for Learning Cooperative Visual Dialog Agents using Deep Reinforcement Learning

📅🇨🇳 中国法定节假日数据 自动每日抓取国务院公告

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

Repository for paper "SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference"

How to build RNNs and LSTMs from scratch with NumPy.

Python wrapper for evaluating summarization quality by ROUGE package

基于深度学习的自然语言处理库

Important paper implementations for Question Answering using PyTorch

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

QANTA Quiz Bowl AI

Examine two sentences and determine whether they have the same meaning.

Automatically extract chemical information from scientific documents

A Library to parse natural language in pure Clojure and ClojureScript

The CRF Layer was implemented by using Chainer 2.0. Please see more details here: https://createmomo.github.io/2017/09/12/CRF_Layer_on_the_Top_of_BiLSTM_1/

Chinese Biomedical Language Understanding Evaluation benchmark (ChineseBLUE)

NLP progress in Fintech. A repository to track the progress in Natural Language Processing (NLP) related to the domain of Finance, including the datasets, papers, and current state-of-the-art results for the most popular tasks.

💙 Emoji handling and meta data for spaCy with custom extension attributes

👩‍🏫 Advanced NLP with spaCy: A free online course

A natural language date parser in Swift (ported from chrono.js)

Ruby SDK for Dialogflow

Cantonese Linguistics and NLP in Python

Japanese negative positive classification.日本語文書のネガポジを判定。

Implementation of the paper Tree Transformer

Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.

A Ruby natural language processor.

A JavaFX based desktop search application.

Character-level Convolutional Neural Networks for text classification in PyTorch

This repository is for my students of Udemy. You can find all lecture codes along with mentioned files for reading in here. So, feel free to clone it and if you have any problem just raise a question.

阿里天池首届中文NL2SQL挑战赛top6

R client for the Google Translation API, Google Cloud Natural Language API and Google Cloud Speech API

Machine learning models to automatically summarise scientific papers

互联网大厂面试经验

This repository contains landmark research papers in Natural Language Processing that came out in this century.

Worth-reading papers and related awesome resources on aspect-based sentiment analysis (ABSA). 值得一读的方面级情感分析论文与相关资源集合

Implementation of Siamese Neural Networks built upon multihead attention mechanism for text semantic similarity task.

Official Python client for the MonkeyLearn API. Build and consume machine learning models for language processing from your Python apps.

Code for the ACL 2018 paper "Neural Document Summarization by Jointly Learning to Score and Select Sentences"

Pre-Trained Models for ToD-BERT

Stanford NLP group's shared Python tools.

📚Survey of previous research and related works on machine learning (especially Deep Learning) in Japanese

Data augmentation for NLP

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

LexPredict ContraxSuite

Code for Learning to select data for transfer learning with Bayesian Optimization