6 Best Natural Language Processing Software & NLP Tools 2023

natural language procession software

I’ve always had a fascination with the intricacies of human language, from the rhythm of a well-crafted sentence to the subtle cues that reveal our emotions. These elements are the foundation of human communication, the core of our connection with others. But what if we could teach a machine to understand human language data, to engage with us in a meaningful conversation? That’s where Natural Language Processing (NLP) comes in.

In my journey to understanding this exciting field, I’ve come across a plethora of NLP tools and software. From the Natural Language Toolkit (NLTK) to advanced sentiment analysis tools, these applications are revolutionizing how we interact with machines. If you’re as intrigued as I am, stick around as I share my top picks for the best Natural Language Processing software and NLP tools that are making waves in the tech industry.

What Are The Best Natural Language Processing Software & NLP Tools?


Key benefits

  1. Python Compatibility: NLTK is a Python library, meaning it’s designed to seamlessly integrate with your Python programs. If Python is your language of choice, you’ll love NLTK.
  2. Resource-Rich: NLTK comes with an abundance of resources. It provides over 50 corpora and lexical resources, perfect for your data analysis needs.
  3. Wide Array of NLP Tasks: Whether you’re looking to do part-of-speech tagging, sentiment analysis, or entity recognition, NLTK has got you covered. It supports a broad range of NLP tasks.
  4. Educational Resource: NLTK is not just a tool; it’s also a learning platform. It’s accompanied by a lot of tutorials and detailed documentation, making it an excellent resource for beginners.
  5. Community Support: Being open-source, NLTK has a large community of users and contributors. You’re not just adopting a tool; you’re joining a community where you can get help and share your knowledge.
  6. Flexible and Customizable: NLTK’s modules are flexible and can be customized to fit your specific requirements, allowing you to fine-tune your Python programs for optimum results.


NLTK is completely free to use. So, you can start leveraging the power of NLP in your projects without any financial constraints.

IBM Watson

Key benefits

  • Natural Language Generation: Leverage the power of IBM Watson’s natural language generation capabilities to transform complex data into human-readable narratives, enabling effective communication of insights, summaries, and reports.
  • Customized Machine Learning Models: Build and train tailor-made machine learning models with IBM Watson, using your own data and leveraging the platform’s expertise to unlock valuable patterns and make accurate predictions.
  • IBM Cloud Integration: Seamlessly integrate your machine learning models and natural language generation capabilities into the secure and scalable IBM Cloud infrastructure, ensuring reliable performance and easy access from anywhere.


You can sign up and try Watson services for free with no time restrictions here.

Amazon Comprehend

Key benefits

  • Powerful Amazon Web Services Architecture: Built on the reliable and scalable infrastructure of Amazon Web Services (AWS), Comprehend offers a robust and secure platform for natural language processing (NLP) tasks. Benefit from AWS’s high-performance computing capabilities and global availability, ensuring seamless operations and data privacy.
  • NLP-Powered Platform: Harness the power of NLP with Amazon Comprehend’s comprehensive suite of features. From sentiment analysis and entity recognition to language detection and topic modeling, the platform empowers you to gain valuable insights from unstructured text data.
  • Pre-Trained NLP Models: Amazon Comprehend provides access to pre-trained NLP models that have been trained on vast amounts of data. These models are ready to use out of the box, saving you time and effort in training your own models. Leverage these models to perform various NLP tasks accurately and efficiently.
  • Customization Options: Tailor the NLP models to suit your specific business needs with Amazon Comprehend’s customization options. Train the models using your own data to achieve more precise and domain-specific results, enabling you to extract valuable insights unique to your industry or organization.
  • Multilingual Support: Overcome language barriers and analyze text in multiple languages with Amazon Comprehend’s multilingual support. The platform can process text in various languages, allowing you to gain insights from global data sources and cater to a diverse user base.


Amazon Comprehend has a unit-based pricing structure that differs for the feature used. It also has a free tier covering 50K units of text (5M characters) per API per month.

Google Cloud NLP API

Key benefits

  • Google Cloud Integration: Leverage the power of Google Cloud’s robust infrastructure and services with Google Natural Language. Benefit from the scalability, reliability, and global availability of Google Cloud, ensuring smooth operations and high-performance NLP capabilities.
  • Advanced Google Cloud Architecture: Google Natural Language is built on top of Google Cloud’s advanced architecture, which provides powerful computing resources, data storage, and security features. This ensures that your NLP tasks are handled efficiently and securely, even when dealing with large volumes of data.
  • AutoML Natural Language: Google Natural Language offers AutoML capabilities, allowing you to create custom NLP models without requiring extensive machine learning expertise. Train and deploy models tailored to your specific use cases, improving accuracy and extracting domain-specific insights from unstructured text.
  • Comprehensive NLP Features: Google Natural Language provides a wide range of NLP features, including sentiment analysis, entity recognition, content classification, and syntax analysis. These features enable you to extract valuable information, gain insights, and automate language-related tasks effectively.
  • Multilingual Support: Google Natural Language supports a variety of languages, allowing you to analyze text in different languages and cater to a global user base. This multilingual support enables you to extract insights from diverse data sources and operate in a global context.


You can start for free and get $300 in free credits to spend on Natural Language. You’ll also get 5,000 units for analyzing unstructured text free per month, not charged against your credits. The monthly prices are unit based but if you use few units per month, you can continue using it completely for free.


Key benefits

  • Easy-to-use Python Library: TextBlob is a powerful and user-friendly Python library that simplifies natural language processing (NLP) tasks. It provides a simple and intuitive API, making it accessible to developers and data scientists, regardless of their NLP expertise.
  • Text Blob Sentiment Analysis: TextBlob offers built-in sentiment analysis capabilities, allowing you to determine the sentiment (positive, negative, or neutral) of a given text. This feature is useful for analyzing customer feedback, social media sentiment, and opinion mining to gain valuable insights.
  • Part-of-Speech Tagging: With TextBlob’s part-of-speech tagging, you can extract grammatical information from text, such as nouns, verbs, adjectives, and more. This feature is helpful for various NLP tasks, including text classification, information extraction, and syntactic parsing.
  • Noun Phrase Extraction: TextBlob can extract noun phrases from text, providing you with a useful technique for identifying and grouping relevant terms or concepts within a given document. This feature is valuable for tasks such as topic modeling, document summarization, and keyword extraction.
  • Machine Translation: TextBlob includes a simple interface to popular machine translation services such as Google Translate and Microsoft Translator. This allows you to easily translate text from one language to another, facilitating cross-language communication and expanding your reach.
  • Extensibility: TextBlob is built on top of the robust and extensive Natural Language Toolkit (NLTK) library for Python. This means you can leverage the power of NLTK’s extensive tools and resources in conjunction with TextBlob, providing you with a wide range of additional NLP functionalities.


TextBlob is free.


Key benefits

  • Powerful Data Analytics: MonkeyLearn provides robust data analytics capabilities, allowing you to extract valuable insights from text data. Whether you’re analyzing customer feedback, social media comments, or survey responses, MonkeyLearn helps you uncover patterns, trends, and sentiment to make data-driven decisions.
  • Advanced Text Analysis: With MonkeyLearn, you can perform advanced text analysis tasks such as sentiment analysis, topic classification, entity recognition, and keyword extraction. These features enable you to understand the meaning and context within your text data, providing deeper insights and actionable information.
  • Customizable Machine Learning Models: MonkeyLearn offers the ability to create custom machine learning models specific to your domain and industry. You can train the models using your own data, tailoring them to your unique requirements for more accurate and relevant results in text analysis.
  • Easy Integration: MonkeyLearn provides seamless integration options, allowing you to incorporate their text analysis capabilities into your existing workflows and applications. This integration streamlines the process of analyzing text data and helps automate repetitive tasks, saving time and resources.
  • Scalability and Performance: MonkeyLearn is designed to handle large volumes of text data, ensuring scalability and performance even when processing substantial amounts of information. You can rely on MonkeyLearn to efficiently analyze and derive insights from vast datasets, regardless of their size.
  • User-Friendly Interface: MonkeyLearn offers a user-friendly interface that simplifies the process of text analysis. You don’t need extensive technical expertise to use their platform effectively, making it accessible to a wide range of users, from data scientists to business professionals.


Their main plan which gives you 10k queries per month costs $299/month.

What Are Natural Language Processing Software & NLP Tools?

If you’re anything like me, you might be asking, “What exactly are Natural Language Processing (NLP) software and NLP tools?” Well, let me break it down for you. At its core, Natural Language Processing (NLP) is a branch of artificial intelligence that gives machines the ability to read, understand, and derive meaning from human language. It’s like teaching a machine to read between the lines, to comprehend the nuances of human conversation, and even to perceive the emotions hidden in our words – a process known as sentiment analysis.

A prime example of an NLP tool is the Natural Language Toolkit (NLTK). This is an open-source library for Python, designed to work with human language data. It provides easy-to-use interfaces and is equipped with over 50 corpora and lexical resources. NLTK is like a Swiss Army Knife for anyone dabbling in NLP, offering tools for everything from sentiment analysis to semantic reasoning.

When we talk about these software and tools, we’re really talking about a new frontier in our interaction with technology. These are the bridges we’re building between human language and machine understanding. And the exciting part? We’re only just beginning to explore the potential.

What is an example of NLP system?

You may be wondering, “What does an NLP system actually look like?” Let me tell you about a time when I first encountered a practical example of a Natural Language Processing system. Remember when you first asked Siri, Alexa, or Google Assistant a question, and you got a relevant answer? That’s a classic example of an NLP system in action.

These virtual assistants use sophisticated algorithms and a whole lot of data analysis to understand and respond to your commands. This process involves several NLP tasks, one of which is ‘part-of-speech tagging’. This is where the system identifies whether a word in your command is a noun, verb, adjective, and so on. Once it has tagged the parts of speech, the system uses this information to understand the sentence structure and the intent behind your command.

But the magic doesn’t stop there. These systems also employ ‘natural language understanding’. This is the process where the system comprehends the meaning of your words in the given context. So, when you ask Siri to “play the latest Taylor Swift song,” it not only understands the words but also the meaning behind them – that you want to hear music from a particular artist.

So, the next time you ask your virtual assistant a question or give it a command, remember you’re interacting with a finely-tuned NLP system that’s analyzing and understanding your language in real-time. Isn’t that amazing?


The world of natural language processing (NLP) software and tools offers a wide range of powerful solutions. Whether it’s IBM Watson’s customized machine learning models, Google Natural Language’s integration with Google Cloud, or the simplicity of the TextBlob library, these tools empower users to extract insights, automate tasks, and make data-driven decisions. By choosing the right NLP software and tools, you can enhance customer experiences, improve efficiency, and unlock the true potential of your text data. Embrace the possibilities of NLP and dive into the world of language processing for transformative outcomes.

Please follow and like us:

Similar Posts