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Top 10 Natural Language Processing Tools in 2023

neww writer

@newwwriter

April 11, 2023

Tech for Good

373

Most Useful Natural Language Processing You Must Learn in 2023

Natural Language Processing is a sub-branch of Artificial Intelligence that deals with computational linguistics and statistical analysis. The main aim of Natural Language Processing Tools is to make computers understand and interpret human language. NLP works to understand human language by processing and analyzing human voice and textual data.

Analyzing large unorganized data is a challenging task in businesses; this is made easier by Natural Language Processing tools. This helps companies to understand customer behavior and market trends with accurate results. Today NLP has applications in AI chatbots, voice assistants, predictive text or speech, etc.

Using NLP tools, machines can now analyze larger amounts of data without being biased and inconsistent. This enhances the speed and accuracy at which data is explored. Let’s learn more about NLP tools in this article.

Natural Language Processing Tools

Natural language processing tools can be used through open-source libraries or software as a service (SaaS). Open-source NLP tools are freely accessible and allow you to customize NLP tools whereas, SaaS is fully paid and comes with ready-to-use NLP tools that require low or no code. Here are the popular and most-used open-source NLP tools:

Python-Based Tools:-

Natural Language Tool Kit (NLTK)

NLTK is a Python library and has fully featured tools. It offers many features such as tokenization, tagging, classification, a bag of words, stemming, etc. Textual data is stored in the form of strings, and hence it can integrate with other frameworks. It supports many languages and provides a user-friendly interface to text-processing libraries. This tool is mostly used in Education and research fields.

MonkeyLearn

MonkeyLearn is an NLP-based tool that can quickly extract and recognize data. It involves pre-trained models that perform content classification, keyword extraction, and sentiment analysis. MonkeyLearn can also be integrated with Excel and Google Sheets to analyze text.

spaCy

spaCy is an NLP-based tool. It is well-documented, fast, and easy to use. It is developed to support large amounts of data. It represents every data as an object and helps in developing a simplified interface to build applications. This helps in connecting with other frameworks and data science tools. It doesn’t support many languages as NLTK does.

TextBlob

TextBlob is an extension of the NLTK tool. It performs the NLP tasks with a more user-friendly interface. It is easy to learn and an excellent choice for beginners. It is mostly used in smaller projects that don't require super fast performance.

Node-Based Tools:-

ReText

ReText is part of a unified tool. It offers multiple tools and plugins that can integrate and work simultaneously. It doesn’t expose its underlying techniques and uses different plugins to achieve desired results. It is easier to perform tasks such as spelling checks, typography corrections, and sentiment analysis detection.

NLP.js

It is a fantastic tool for beginners to learn Natural Language Processing in Artificial Intelligence. It is built on several NLP libraries. It offers a rich interface with features such as natural language generation, named entity recognition, and sentiment analysis. It supports a few languages, which can be helpful if you are working on languages other than English.

Compromise

This is not a great tool in NLP tools, but this is a good option if you are looking for a good-performing tool that offers a wide range of features and functions. It works well on the client side. If you are focused on a small package delivering specific functionalities, this is an effective tool to be considered.

Java-Based Tools:-

OpenNLP

This tool is hosted by the Apache Foundation. Working on Apache projects such as Apache NiFi and Apache Spark is easier. It is a simple NLP tool that involves processing components of NLP. It supports several languages. If you are working on Java projects, OpenNLP is an excellent tool that offers a wide range of features.

Stanford CoreNLP

Stanford CoreNLP is an effective tool that offers a wide range of NLP features. This involves deep learning, statistical, and rule-based NLP functionalities. This tool is mainly developed for research and experimentation. It was developed by a top research institute however it may not be the best choice for production workloads.

10. CogcompNLP

It is a great tool used for text processing remotely or locally, reducing the burden on local storage. It offers processing functions such as tokenization, part-of-speech tagging, chunking, named entity tagging, labeling, etc. This tool is an excellent choice for research, and it has many features to explore.

The End

From this blog, we have learned about open-source Natural language processing tools. These NLP tools can be used effectively to improve your business. If you want to learn more about Natural language processing and Artificial Intelligence you can check out our other blogs.

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