As technology advances beyond their artificial constraints, organizations are searching for fresh ways to take advantage. A knifelike increase in computing speeds and potentialities has guided to new and supremely intelligent software systems, a few of which are ready to replace or augment human services. Natural Language Processing — the application of software systems for analyzing, understanding and correctly responding to speech is viewed as the next big bounce in user interface technology. Language is a method of communication with the help of which we can speak, read and write but computers don’t speak languages the way humans do. They usually communicate in machine language while we speak human language. That is when Natural Language Processing comes in.
NLP is a field of Artificial Intelligence that makes human language intelligible to machines by giving computers the ability to read, understand and derive meaning from human languages such as English, Hindi, Spanish, etc.,It helps developers to build and arrange knowledge to perform tasks such as speech recognition, translation, topic segmentation and much more.
The Growing Importance of Natural Language Processing:
In the past, computers could only work with languages which are structured and the language had to be precise and unambiguous. To program a computer and to conduct any task, you had to give it clear directions. You could only use the limited number of commands that the computer can understand and the syntax had to be perfect as well.NLP assures to eliminate the requirement for being so precise as instead of having to learn the computer’s language, the computer will learn how to understand ours.
As the quantity of data accessible online is elaborating day by day, the requirement to access and process it turns out to be extremely important. NLP helps in managing large amount of data via cloud or distributed computing at an exceptional speed. Human language is extremely complex and diverse. There are not only hundreds of languages and dialects but inside each language is a sole set of grammar, syntax rules and terms. NLP is significant in the light of the fact that it helps in resolving ambiguity in language and removes the communication barrier that always exists between machines and humans.
Applications of Natural Language Processing:
Language Translator: Machine translation (MT) is one of the most significant applications of NLP which is the method of transforming one language or text into another keeping the meaning unaltered. Manual translation means translating information from one language into another and when the same thing is done by a machine, we call it as “Machine” Translation. The concept behind MT is to develop computer algorithms to allow automatic translation between languages without any human intervention. The best-known application for machine translation is well-known “Google Translator”.
Speech Recognition: Recently the advances in NLP has started voice as the technique of giving inputs to the system other than typing, clicking or selecting text. Now we have a whole variety of speech recognition software programs that grants us to decode the human voice. Voice Assistants like Cortana, Siri, Google Assistance, Amazon Alexa are some of the perfect examples of how machines are trained to recognize the human voice, analyse the intent, and respond correspondingly. Google Voice Search is one more example of speech recognition wherein the users give voice input to conduct the search.
Sentiment Analysis: Organizations use sentiment analysis, to investigate opinions and sentiment online to assist them find out what customers actually think about their products and services. Sentiment analysis helps businesses to find out the sentiment of a customer towards services, brands, or products in online feedback (positive, negative, neutral).
Chatbots: NLP has become the essence for making chatbots, and despite such systems are not so flawless they easily can manage standard tasks. As interacting with every customer manually and resolving the problems can be a tedious task chatbots helps the companies in achieving the goal of smooth customer experience. It saves customers from the frustration of waiting to interact with customer call assistance guiding them to suitable resources and products at any time.
Grammar Checkers: This is one of the most widely used applications of natural language processing that coordinates with a variety of text documents, automatically checks for spelling errors as the user continues to write, and suggest corrections. One of the popular examples is Grammarly that scrutinizes your text for all types of mistakes, sentence structure problems and further more.
Natural language Processing: Game changer and future of Business
The future with NLP is exciting and the cause behind this is its capacity to extract insights from human texts and interpret human emotions exactly. NLP can decode human emotions and distinguish emotions like happy, sad, joy, angry etc. As we know emotions operate customer choices and companies must track these emotions and analyse the customer better to deliver them with improved services. By using NLP,Companies can establish voice interfaces and Chatbots that can talk with customers anytime and every time. And these interfaces have the potential to understand customers’ voice and reply to their queries with relevant solutions. NLP also aids in identifying customer preferences through browsing history, social media pages, keyword searches and then sorting them into different buyer characters to create ad campaigns specific to the characters. Thus, NLP is gaining advantage in business activities slowly aiding businesses to stay forward in competition by better operational efficiency, faster resolutions and more individualized customer engagement.
Wrapping it up: Why is Natural Language Processing Difficult?
The nature of the human language is what makes NLP difficult. When humans communicate with each other, problems like mispronunciation are easily understood but computer isn’t as objective as a human and has a tough time differentiating between relevant information and inconsequential words. For example, telling someone you are engaged can mean a lot of things like you are going to be married or busy with a project or involved in a lengthy process. Furthermore many words have different meanings; depending on how they are used which computers are still trying to understand. Another problem is mumbling, talking too quickly or too slowly, adding “ums” and “ahs” which may be natural for humans to use in sentences but difficult for the computer to decode the meaning. Any difference from the computer’s fixed way can result in error messages or a wrong response.
Although there is more research required and the technology is still evolving but NLP is a very demanding and promising field of the 21st century. It is transforming the way we analyze and interact with language-based data and perform automated tasks like translation, classification, and extraction. The future is going to see some massive changes as the technology becomes more mainstream and more advancement in the ability are explored.