Natural Language Processing: A branch of artificial intelligence that helps computers understand, interpret, and manipulate user language is known as Natural Language Processing(NLP). It pursuits to fill the gap between humans and computers. It had been drawn from many disciplines, including computer science and computational linguistics.
There is a rapid advancement in this technology. The reason behind this is the increasing popularity and requirement of human-machine communication. The availability of big data, powerful computing, and enhanced algorithms also accounts for this.
With computing technology going beyond all its artificial limitations, Organizations are exploring new advantages. This has only led to the development of this highly intelligent software system. These systems are ready to replace human services in many spheres.
The super-smart chatbots solving our daily problems are one of the best examples of the rise of NLP. If you say, “Alexa, I like this song”. Alexa will save the feedback and reply in a human-like voice. It then adapts to play that song along with similar ones.
When we analyze the interaction we know that the device activated when it heard you speak. It absorbed the unspoken intent from the contents of the speech. It acted on that speech as it analyzed the command. It also gave feedback in a well-formed sentence in English. The entire interaction took place in less than 5 seconds. This interaction was made possible with the help of Natural Language Processing. It employs AI elements like machine learning and deep learning.
The NLP Algorithm
NLP employs many different techniques to understand user language. The Basic NLP approaches are tokenization and parsing, lemmatization/stemming, part-of-speech tagging, language detection, and identification of semantic relationships.
The other underlying tasks are often used in higher-level NLP capabilities, such as:
- Content categorization
- Topic discovery and modeling
- Contextual extraction
- Sentiment Analysis
- Speech-to-text and text-to-speech conversion
- Document Summarization
- Machine Translation
The prevailing goal in all of these is to take raw language input and produce a high-value response.
Why is Natural Language Processing important?
Natural Language Processing allows the computer systems to interact efficiently with the users. It also processes other language-related tasks. It makes it possible for machines to read the text, hear speech, interpret, recognize the sentiment, and determine the key content.
Because of NLP, today’s computers can understand humans better than fellow humans do. They are completely structured to replace human services. They analyze language-based data with consistency and without fatigue. They also have unbiased feedback.
We know that human language is very complex and diverse. There are infinite possibilities of expression. Be it verbal or in writing, makes no difference. The difficulty adds up with the presence of the numerous languages and dialects. Every language equipped with unique grammar and syntax. Moreover, whenever we write, we often misspell, abbreviate, and omit punctuation. While speaking, we often mumble, stammer, and mispronounce words. This makes it very difficult for simple computing to understand.
Thus, to model human language it is very necessary to have a paradigm like this. A paradigm that has a capability of syntactic and semantic understanding. Something that s not present in the simpler machine learning approaches. This is where NLP comes into play.
There are uncountable benefits of Natural Language Processing. It is leveraged by many companies to improve the efficiency of customer interaction. It also allows them to lubricate documentation and data-analysis processes. They are employed to improve the accuracy of documentation. They also help in finding the most persistent information and command. It recognizes its workflow schema from a large database of information.
Computers can understand and analyze user language better with NLP. They infer the input with more meaning rather than simply digesting and outputting programmed responses. In essence, it offers better interaction and communication with computer systems to human beings.
The most important sector of NLP usage is Chatbots. They integrate with the messenger apps and serve the users with their queries. They employ NLP and other machine learning paradigms to give the user the best feedback. They detonate when we speak or type a trigger phrase. Then they receive the user command. They analyze it and produce a relevant output as per the previous choices and user like.
Natural language processing caters to both ends of a transaction. (i.e. the buyer and the seller.) They give easier solutions to customer problems. This is made possible with better understanding and clear communication. It also reduces human labor by replacing human understanding of an input. It replaces it with a better and pocket-friendly alternative.
Moreover, NLP also plays a vital role in the functioning of our virtual assistants. Imagine a day without the Google Assistant, Alexa, or Siri. This is where NLP becomes the need of the hour.
Natural Language Processing has been the technology from the past and the technology for the future. With the advanced growth of technology today, they serve as a necessity in diversity. It plays a key role in every AI-driven program. It is establishing the future of the human-machine relationship.