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- Insights
- Cryptocurrencies
- Stocks
- White Papers
- Industry
- Geography
Language is a human's in-built mechanism that helps him communicate with others effectively. People can use language to write, read, and speak and most importantly, naturally convey their plans and decisions. But looking into the digital world, computers are very different. Despite the evolution in artificial intelligence, machines still struggle to understand us when we communicate in our native tongue. Therefore, researchers and scientists have come up with a disruptive technology called Natural Language Processing (NLP) to ensure that machines understand human language. The applications of natural language processing are being deployed to make computers understand unstructured and often ambiguous human speech.
Machines are extremely different from humans. Forget language, they can't even carry out simple tasks if humans don't program them. Similarly, computers speak in code, using long lines of numbers, and programming languages. On the other hand, humans are naturally flawed to run their mouths. We can speak in different languages and even add sarcasm to our words, which could be extremely difficult for machines to understand. But the concept of developing artificial intelligence technologies is to come up with disruptive solutions that could patch the human-machine gap. While the automation of things we use in our everyday work has eased our burden, real-world applications of NLP is also supporting humankind to connect with machines in a simpler way. Natural language processing is an artificial intelligence-based solution that helps computers understand, interpret and manipulate human language. It goes through large datasets to figure out humans' way of talking. While sophisticated machines might conjure images of futuristic robots, there are already basic applications of natural language processing at work in our daily lives.
'Did my device just hear me?' This is a question that we often hear from people who are unfamiliar with natural language processing. Yes, your device heard you and it will now suggest whatever you wanted. Promoting content based on what consumers want is a trendy way of delivering next-generation business. Business organizations and online sellers use social media platforms to carry out these kinds of promotions. They use technology to understand consumers' shopping habits, predict product demand, or monitor trends to target marketing messages. Besides, they use natural language processing to analyze people's needs when they talk or type the content. Later, the online sellers provide suggestions on products you might prefer to buy.
Out of the 195 countries in the world, only 67 have recognized English as an official language. Not all of them can speak and write fluently without grammatical errors. Fortunately, natural language processing comes to the rescue of those who stumble to deliver their thoughts in proper form. NLP is widely used to check grammatical errors in the input text. They help in language learning, text authoring, and other scenarios. A grammar checker makes the correction process accurate, effective, and faster with the help of NLP. For example, famous writing tools like Grammarly and ProWritingAid are a couple of real-world applications of natural language processing that people use in their routine.
How will you sort between necessary and promotional or advertising emails if they are heaped up in your inbox without any remarks? Scary, isn't it? Fortunately, natural language processing is a magic tool that helps sort spam messages by uncovering certain words or phrases that signals them. Email filters are one of the early adopters of NLP. But as technology evolved, the filtering also got upgraded. Today, NLP carefully delivers sorts and adds our mails in three categories namely primary, social, or promotions.
'Hey, Siri,' has turned out to be the slogan of the century. Besides Siri, we have Alexa, Cortana, and many others lined up to assist us in our everyday processes. These digital assistants use voice recognition and natural language processing to decode the speech, extract the meaning, and reply with words or actions as per the needs. As we step into a far-fledged future of machines that can interact with humans, researchers are working on digital assistants that could understand contextual clues from humans. This will act as a foundation stone to streamline NLP that understands the sarcastic way of human communication.
Data is the power behind many companies. But the immediate hurdles they face after collecting data are to convert them to a uniform format and use them to obtain meaningful insights. As a result, many organizations seek help from NLP and text analytics to assist them to turn their unstructured data into insights. They help categorize content based on names, dates, currency values, and even phone numbers. Later, they use the classifications to seek out important information.
