Natural Language Tools & Services

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• Natural Language Processing (NLP)
• NLP Tools | Wikipedia
• Auto-tagging
• Machine Translation reading list & open-source toolkits | Tsinghua Natural Language Processing Group
• Statistical natural language processing and corpus-based computational linguistics: An annotated list of resources | Chris Manning - Stanford
• Software Packages | Cognitive Computation Group, led by Prof. Dan Roth
• PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM | gitHub
• NLP Tool Finder | NIH University of Utah DBMI
• API-based Services
• Natural Language Processing and Machine Learning in JavaScript | David Luecke - Medium
• Top 22 NLP (Natural Language Processing) APIs for Developers in 2018 | RapidAPI
• Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review | K. Kreimeyera, M. Foster, A. Pandeya, N. Aryaa, G. Halford, S. Jones, R. Forsheea, M. Walderhauga, and T. Botsisa - Journal of Biomedical Informatics 71 natural language processing systems

Capability with Javascript

• TensorFlow.js for training and deploying ML models in the browser and on Node.js (was called Deeplearnjs)
  • Keras.js No longer active - capability now is in TensorFlow.js
• NLP.js NLP Manager: built on top of several other NLP libraries, including Franc and Brain.js providing Text Classification, Sentiment Analysis, Stemming (Morphological Similarity), Named Entity Recognition (NER), and natural language generation. (nodejs)
• Compromise modest natural-language processing (NLP) interprets and pre-parses English and makes some reasonable decisions
• Natural provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, tf-idf, WordNet, string similarity, some inflections, and more. (nodejs)

Capability (other)

• Google:
  • TensorFlow
  • Google Natural Language - AutoML Natural Language
  • Cloud Speech-to-Text | Google
• Amazon - AWS:
  • Textract | Amazon in the Elastic Stack Architecture
  • Comprehend | Amazon
  • Transcribe | Amazon
  • Amazon Polly | Amazon
• Microsoft - Asure:
  • Azure Cognitive Services | Microsoft
  • Azure Bing Speech API | Microsoft
• CoreNLP | Stanford The Stanford Natural Language Processing Group Toolkit (Python)
• Natural Language Toolkit (NLTK) (Python) implements Text Classification, Tokenization / Sentence Splitting, Stemming (Morphological Similarity), Part-of-Speech (POS) Tagging, Syntax (Parsing), and semantic reasoning
  • TextBlob(Python) is kind of an extension of NLTK. You can access many of NLTK's functions in a simplified manner; includes functionality from the Pattern library
• SpaCy (Python and Cython) everything as an object rather than a string, which simplifies the interface for building applications
  • textacy (Python) focuses primarily on the tasks that come before and follow after SpaCy
• scikit-learn NLP toolkit
• Apache OpenNLP
• fastText | Facebook's AI Research representations and text classifiers (Python)
• MALLET a Java-based package
• Intel NLP Architect (Python)
• Gensim fast Vector Space Modelling, Topic Modeling, LDA implementation (Python)
• flair use pretrained BERT (PyTorch)
• AllenNLP an Apache NLP research library (PyTorch)
• Pytorch-NLP (PyTorch)
• Matlab
• Sintelix
• H2O Driveless AI
• Dandelion API
• VoxSigma API
• Speech Recognition |Twilio
• Automatic Speech Recognition (ASR) | Speechmatics
• Voice API | Nexmo
• wit.ai
• Meaning Cloud
• Haven OnDemand
• Aylien
• Lexalytics
• Dialogflow
• Indico
• TextRazor
• Intellexer
• Meaning Cloud
• LSTM and QRNN Language Model Toolkit for PyTorch | GitHub
• Thematically Discover
• Pattern (Python)
• Polyglot
• Speech to Text | IBM
• Text to Speech | IBM
• Watson Natural Language Understanding | IBM
• Project Debater | IBM

Text Labeling

• Bella open tool aimed at simplifying and speeding up text data labeling. Usually, if a dataset was labeled in a CSV file or Google spreadsheets, specialists need to convert it to an appropriate format before model training. Bella’s features and simple interface make it a good substitution to spreadsheets and CSV files. A graphical user interface (GUI) and a database backend for managing labeled data are Bella’s main features.
• Tagtog choose three approaches: annotate text manually, hire a team that will label data for them, or use machine learning models for automated annotation.
• Dataturks provides training data preparation tools. Using its products, teams can perform such tasks as parts-of-speech tagging, named-entity recognition tagging, text classification, moderation, and summarization.
• Brat rapid annotation tool] a web-based tool for text annotation; that is, for adding notes to existing text documents, designed in particular for structured annotation, where the notes are not freeform text but have a fixed form that can be automatically processed and interpreted by a computer.
• Yedda a lightweight Collaborative Text Span Annotation Tool developed for annotating chunk/entity/event on text (almost all languages including English, Chinese), symbol and even emoji.

• Automated Scoring