TechDogs-"Natural Language Processing (NLP) Software 101"

Emerging Technology

Natural Language Processing (NLP) Software 101

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Overview

One of our favorite pop culture characters is the Terminator. If you’re a film fanatic like us, you may know him better than the T-800! This humanoid robot has done everything possible – traveled through time, saved John Connor and sacrificed himself for the greater good. However, being tech heads, we have always wondered about the technologies that powered the Terminator – especially the systems that allowed him to interact with humans.

We mean, he did give us a hint when he said, “My CPU is a neural-net processor, a learning computer, that Skynet presets to READ only when we are sent out alone.”

So, it is obvious that he utilizes the time he spends around humans to better grasp how we communicate. While it may sound like something from a movie (duh!), in the modern age, robots are actually learning – and improving – when it comes to people-computer interaction. Yes, it has something to do with Artificial Intelligence – but that’s just the tip of the iceberg.

Hop on as we join the Terminator to terminate the confusion by exploring Natural Language Processing (NLP) Software!
TechDogs-"Natural Language Processing (NLP) Software 101" There Must Be A Better Way To Learn Human Languages!
We’re sure you’ve heard of or used AI-based writing tools before – does ChatGPT sound familiar? Earlier, humans could only communicate with computers using programming languages and codes. However, today, computers can understand and respond in our native language. So, how did this advancement take place – the answer is Natural Language Processing (NLP) Software!

Before moving ahead, let’s understand what NLP means. Natural Language Processing (NLP) is an application of Artificial Intelligence. By leveraging AI models, computers can understand the text and spoken words, in the same way, we humans can. You may already have interacted with NLP applications such as voice-operated GPS, digital assistants on smartphones or customer support chatbots on websites.

Moving on, Natural Language Processing Software is a solution that helps businesses build bots that can understand and respond to text/voice input with responses of their own. We’re pretty sure even Cyberdyne Systems used NLP Software to develop the T-800.

So, join us as we explore all about NLP Software!
 

A Brief Look At Natural Language Processing (NLP) Software


Natural Language Processing (NLP) Software helps computers understand, interpret and manipulate human language (in the form of speech or text) through Artificial Intelligence. NLP Software uses a combination of computational linguistics and machine learning models to process human language, understand the speaker’s intent, process the user’s request and then give an output back in human language.

For example, NLP Software can help develop tools to translate text from one language to another, summarize large volumes of content, respond to spoken commands and more. Hence, this tool sees application in digital voice assistants, speech-to-text software, chatbots, voice-activated systems, etc.
As you may have guessed, this emerging tech has not been around for long. Let’s see how it came about!
 

Evolution Of Natural Language Processing Software


A major part of the development of NLP Software was the evolution of NLP technology itself. Only in the last decade did we create software applications that could help us deploy NLP as an integrated service. Here’s a brief timeline of the evolution of NLP Software: 

The concept of Natural Language Processing stemmed from the need to develop Machine Translation in the 1940s. This would allow us to translate text from one language to another.

Later, in 1952, Bell Labs developed Audrey, the first speech recognition system that could interpret all ten numerical digits. However, it was abandoned as entering phone numbers manually was quicker.

In 1962, IBM built a shoebox-sized machine that could recognize up to 16 words.

In 1971, Defense Advanced Research Projects Agency (DARPA) developed Harpy at Carnegie Mellon. It became the first computer system to recognize over a thousand words.

ELIZA, a chatbot program was developed between 1964 to 1966 at the Artificial Intelligence Laboratory of MIT by Joseph Weizenbaum. Many consider it to be the first Natural Language Processing computer program ever developed. It was one of the first programs that could attempt the Turing test.

Innovations in Natural Language Processing gained momentum in the 1980s when real-time speech recognition became feasible due to advancements in computing and data processing technologies.

Several advancements followed since then. Most notably, in 2022, the world was stunned by ChatGPT; an AI-powered Natural Language Processing (NLP) application developed by OpenAI that could write human-like answers in real time for a variety of queries. It also paved the way for NLP Software and its applications to enter the mainstream.

TechDogs-"Evolution Of Natural Language Processing Software" A GIF From The Terminator Movie Franchise
Okay, we get it, T-800! Let’s get back to the present and take a look at its working, which would have amazed even its early pioneers.
 

How Does Natural Language Processing (NLP) Software Work?


If you use Siri, Alexa and other voice assistants, we bet you must have wondered how they worked. (Well, you can ask them – those nifty NLP applications know the answer to nearly everything!). Such applications bridge the communication gap between computers and humans in real time which is made possible by NLP Software working in the background:

To achieve this, NLP Software relies on Deep Learning and Machine Learning algorithms to interpret and understand human language input. In some cases, it can even predict a human’s intention and purpose while the text is being input. (We don't have to tell you about auto correct on your smartphone, right?)

Deep Learning models ingest unstructured textual data and convert it into structured and usable data. Machine Learning (ML) algorithms then use analytical and statistical methods on this data to understand the intent of the user. Using a combination of highly advanced ML models, associations between words are recognized and the NLP application provides succinct answers or insights based on its knowledge bank. Additionally, the better the training, the vaster the knowledge bank, which leads to more accurate and intuitive outputs.

This process can be further broken down into 4 steps:
 
  • Tokenization

    The text is broken down into semantic units (single clauses or words).

  • Stop Word Removal

    Words that add no unique information are removed (“the”, “an”, etc.)

  • Stemming/Lemmatization

    Transforms the remaining words to their root form to assess the context in which the word is used. (“Changing” becomes the root word “change”).

  • Speech Tagging

    A trained model tags the words according to grammatical case (nouns, verbs, etc.). 


Well, T-800, we hope you now understand how your inbuilt NLP system works.

TechDogs-"How Does Natural Language Processing (NLP) Software Work?" A Funny GIF From The Terminator Movie Franchise
Let’s look at some applications of NLP – and no, we do not mean you, Mr. Terminator!
 

Applications Of Natural Language Processing (NLP) Software


Allowing a computer to understand human language and respond the same way is revolutionary. Several industries and domains have adopted this technology into applications including:
 
  • Social Media Sentiment Analysis

    NLP Software has grown in importance as a business strategy for extracting hidden insights from social media platforms. Sentiment analysis can help extract sentiment and emotion in response to products, promotions, campaigns, events, etc. from the language used in social media responses, reviews, comments, etc. Companies can then utilize these insights to enhance their product designs, marketing initiatives and outbound communications.

  • Text Summarization

    Text summarization uses NLP techniques to digest huge volumes of digital text and create summaries for search indexes or for readers who don't have time to read the full text. Text summarization uses features such as semantic reasoning and natural language generation (NLG) to add useful context and conclusions to summarize the entire text. Yes, you can now get the gist of this article in 300 words - although that would make our writers sad!

  • Email Spam Detection

    You may not connect spam detection with NLP, yet the best spam detection tools deploy NLP Software for text classification capabilities. They scan emails for language that often indicates spam or phishing, such as characteristic poor grammar, threatening language, inappropriate urgency, misspelled company names and more.

  • Big Data Extraction

    NLP Software enables businesses to automate the extraction of information from documents or websites which can be converted into a specified format. This streamlines data operations and saves time.

  • Voice Assistants

    Yes, talking of Siri and Alexa here! Using NLP Software on the backend, these bots have become a bridge between humans and Internet-based services as they can provide all manner of answers and responses through voice interaction.


Hey Siri, what’s the next section?

Well, reader, now that you know about the applications, here are the benefits of using NLP Software (to be read in Siri’s voice!).
 

Benefits Of Using Natural Language Processing (NLP) Software


You can bet that this modern technology has blessed us with the ability to tackle many challenges. Here are a few of the benefits that NLP Software offers:
 
  • Streamlines Business Processes

    NLP technologies enable businesses to automate and streamline their procedures. Processing data manually takes time and is prone to human error. Instead, NLP Software enables businesses to automate the analysis and extraction of consumer data, giving employees more time to work on higher-priority tasks.

  • Improves Customer Experiences

    For businesses trying to enhance customer service and experience, NLP Software can be highly valuable. The software can automatically categorize and evaluate customer queries/ complaints – whether they are in the form of text, images or speech. This can then be used to assign a suitable customer support agent immediately or to deliver a real-time response. Customer satisfaction rates hence improve, thanks to streamlined support and timely assistance.

  • Enhances Business Insights And Innovation

    To glean business insights from unstructured data, such as responses and online reviews, a high level of analytics is necessary. Tools with NLP capabilities can be trained to understand the content and analyze the data more quickly than humans. Businesses can hence use NLP technologies to process massive volumes of unstructured customer data to gain and apply insights to decision-making.


Now that you know about the primary benefits of NLP Software, let’s run toward the future!

TechDogs-"Benefits Of Using Natural Language Processing (NLP) Software" A GIF From The Terminator Movie Franchise  

What’s The Future Of Natural Language Processing (NLP) Software?


The NLP Software market size is expected to increase exponentially from USD 20.80 billion in 2021 to roughly USD 161.81 billion by 2029. As NLP Software becomes more intelligent, human-computer interaction will soon give way to human-computer conversation. This means NLP Software will quickly replace manual processes such as analysis, comprehension of text and creating tailored responses.

Moreover, NLP is now focused on human language but will eventually integrate non-verbal communication, including sign language, gestures and facial expressions. This will lead to the development of collaborative robots (cobots) that will speak like humans and work alongside us in workplaces. Soon, your work colleague could be a T-800 Terminator who can craft the perfect subject lines for your marketing campaigns! #TerminateManualProcesses
 

Conclusion


Natural Language Processing (NLP) Software allows machines to interpret human language. It’s at the core of some of the tools we use every day – from text translation to chatbots to voice assistants. The software allows us to leverage NLP to create intelligent systems capable of understanding and analyzing human language. This streamlines the extraction of meaning, intent and sentiment from text and speech without human intervention.

We hope this article explained all you wanted to know about NLP Software!

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Machine Learning (ML)Natural Language Processing (NLP) Software Natural Language Processing NLP Human Computer Interaction

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