nlpcore is a library for Natural Language Processing core protocols and specs used in other projects.

Go API client for cloudmersive solutions. Currently stands only for NLP(v2) API.

Amazon Japan Help Desk on Twitter

Nlp tools in Java, Python. With examples and installation requirements. Examples focused in spanish language

.NET Core Client for Cloudmersive NLP APIs

Python client for Cloudmersive NLP API

LinTO's NLP core services

PHP Client for Cloudmersive NLP APIs

A simple NLP rest microservice made with python and dockerized @ gigadr3w/nlp-rest

Speech recognition and conversion into speech of any other language

NLP API

Container-first, JSON-configurable, NLP REST service based on Flair

A robust and easy-to-use toolkit for POS (Part of Speech; NLP) tagging. It's approach is to automatically construct tagging rules in the form of a binary tree. Supports pre-trained UPOS, XPOS tagging models for about 80 languages.

Objective-C Client for Cloudmersive NLP APIs

Google Chrome extension analyzing the category of and entities within text in a webpage using the Rosette API.

Ruby Client for Cloudmersive NLP APIs

This project uses a multilingual embedding model to align sentences in one language ( preferably a low-resource language) to their potential paired translation in English. The idea is that if we can crawl documents in both languages online (eg from news sites), we can easily pair up sentences that are translations of each other.

Unofficial minified fastetext API. Use it to run NLP DL models that require word embeddings on the client-side.

This project is a web application that converts text input into speech, providing a convenient and accessible way to transform written content into spoken words. Users can enter text in the provided textarea, click the "Predict" button, and instantly hear the generated speech. The app utilizes Flask for the backend.

The NLP Analysis Toolkit, a Python GUI application that harnesses the power of Natural Language Processing (NLP) to provide insights into text data. This comprehensive tool integrates three key features: Sentiment Analysis, Named Entity Recognition (NER), and Emotion Detection.