Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human (natural) languages. The ultimate goal of NLP is to enable computers to understand and process human language in a way that is similar to how humans do. That’s when NLP tools come into place.
Some typical applications of NLP include language translation, sentiment analysis, and chatbots. It focuses on making it possible for computers to read, understand, and generate human language.
NLP techniques are also used to improve search engines and analyze text data for business intelligence. It involves a combination of linguistics, computer science, and artificial intelligence techniques, including machine learning, deep learning, and rule-based systems.
These techniques are used to analyze and understand the structure and meaning of human language, including the grammar, semantics, and context of the language.
7 NLP Tools and Services to Try in 2023
Many natural language processing (NLP) tools available online can be used for various tasks in 2023. Here are seven examples:
1) IBM Watson
IBM Watson is a suite of artificial intelligence (AI) and natural language processing (NLP) tools developed by IBM.
Some of the NLP capabilities of IBM Watson include text analysis, language translation, and entity recognition.
IBM Watson also includes tools for machine learning and data visualization.
Aylien is a company that provides NLP tools for text analysis and classification.
Some of the features of Aylien’s NLP tools include sentiment analysis, entity recognition, and summarization.
Aylien’s tools can be used for various applications, including social media analysis and content moderation.
Paraphrasetool.ai is a state-of-the-art natural language processing tool that can be used for tasks such as paraphrasing text.
If you find a piece of text difficult to comprehend due to the complexity of words or any other reason, this paraphrasing tool can help you simplify text in a single click.
As a result, you can better understand what is said rather than just reading words without comprehension.
The tool is easy to use due to its simple interface.
MonkeyLearn is a company that provides NLP tools for text analysis and classification.
Some of the features of MonkeyLearn’s NLP tools include sentiment analysis, entity extraction, and topic modeling.
MonkeyLearn’s tools can be used for various applications, including customer service and content moderation.
5) Amazon Comprehend
Amazon Comprehend is a suite of NLP tools developed by Amazon.
Amazon Comprehends features include language detection, sentiment analysis, and entity recognition. It can be used for various applications, including text analysis and machine learning.
This is an open-source library for NLP tasks such as tokenization, lemmatization, and POS tagging.
It is a popular choice for those looking to get started with NLP and is used in developing a wide range of NLP applications.
7) Google Cloud
Google Cloud is a suite of cloud computing and machine learning tools developed by Google.
Some of the NLP capabilities of Google Cloud include language translation, text analysis, and entity recognition.
Google Cloud also includes tools for data storage and analysis, as well as machine learning and data visualization.
What are Possible Future Applications of NLP
There are many possible future applications for natural language processing (NLP). Some potential areas where NLP could be used include:
Virtual assistants and chatbots
NLP could improve virtual assistants’ capabilities, such as Apple’s Siri or Amazon’s Alexa.
These systems could use NLP to better understand and respond to user requests and to handle a wider range of tasks.
NLP could be used to improve the accuracy and speed of machine translation systems, making it easier for people to communicate with one another across language barriers.
People from different parts of the world can communicate with each other.
NLP could be used to improve the efficiency of customer service centers by allowing companies to handle a higher volume of inquiries through automated chatbot that use NLP to understand and respond to customer inquiries.
NLP could be used to help personalize education by analyzing student writing and providing feedback or tailored learning materials.
This can work well to take the educational sector to the next level.
The efficiency of education will increase in the coming future.
NLP could be used to automatically extract information from large volumes of text data, such as news articles or social media posts.
This could be used for tasks such as sentiment analysis or trend analysis.
NLP could extract information from electronic medical records and assist with diagnosis or treatment planning tasks.
This great development can bring a revolution in the healthcare industry.
These tools will take on most of the tasks humans perform in hospitals and other healthcare facilities around the globe.
These are just a few examples of the many possible future applications of NLP.
As the field advances, new and innovative uses for NLP will likely be developed.
As a result, human life is likely to become convenient and efficient.
Why is it Important to use NLP tools?
There are several reasons why it is crucial to use Natural Language Processing (NLP) tools:
NLP tools can help you process large volumes of text data quickly and accurately, saving you time and effort.
You do not have to worry about errors or inconsistencies since NLP tools can care for everything.
NLP tools can help you avoid errors that can occur when processing text data manually.
As a result, you get accurate results without being worried about potential mistakes.
NLP tools can help you extract valuable insights and information from text data, helping you better understand your data.
You do not have to spend hours analyzing the data and extra meaningful information from it.
NLP tools can perform this task for you, eventually saving you a lot of time and effort.
NLP tools can help you make better decisions based on data by providing insights and information you might not have otherwise discovered.
By automating many of the tasks involved in working with text data, NLP tools can help you be more productive and focus on higher-level tasks.
You do not have to waste time focusing on things that require much time.
Instead, you can count on NLP tools to handle time-taking tasks and focus yourself on things that matter the most.
Increased customer satisfaction
By using NLP to analyze customer feedback and support requests, you can identify common issues and concerns and address them more effectively, leading to increased customer satisfaction.
NLP tools can help you translate text from one language to another or generate human-like text, improving communication and understanding between people who speak different languages or use different communication styles.
Overall, NLP tools can help you work more efficiently and effectively with text data, leading to better outcomes and results.
That’s why more and more tools are being developed using natural language processing technology.