Natural language processing (NLP), a subfield of Computer Science, Linguistics, and precisely Artificial Intelligence undertakes how to enable computers to process, manipulate and comprehend natural language data.
It aims to construct machines to interpret text or speech data as well as respond to it in the same way as humans do.
While NLP is not a new science, since technological advancement has thrived, it has enhanced human to machine transmission with the use of massive data and expanded algorithms.
Surprisingly, these days machines comprehend natural language data more than human beings. Understanding human language is complex due to a massive number of languages- each having various dialects, grammatical patterns and each user being able to speak distinctively, it is a machine that analyses the unstructured and complex human language and gives it “numeric structure” and solves obscurity in it.
The principle-based modelling of human language along with statistical machine understanding, and deep learning jointly form NLP.
Altogether this mechanization facilitates computers to make sense of human speech and text entailing sentiments expressed through words.
Efficiently Analyses a Large Database
With so much unstructured documentation around- emails and research findings, etc, it is not a walk in the park to arrange it so that it makes sense. However, NLP has made it easier to process a huge amount of databases and analyse them efficiently. As a result, we get filtered data.
Improve Customer Experience
The bigger the business, the larger the customer base is. However, it’s no longer complicated to get to know what a customer feels for a particular business because enterprise-wide artificial intelligence can provide valuable information to improve customer experience. Whenever a customer drops a query, it gives exact and accurate answers which derive customer satisfaction.
Automation of Tasks
Repetitive tasks- like analysing open-ended survey responses and other textual data that consume a lot of time are automated with the use of Ai systems.�
These systems can be instructed to the language and criteria of your business to perform certain tasks to give accurate and unbiased results.
Reduction in Costs
NLP works at all scales and all time. While doing a manual inspection, requires a substantial staff to perform tasks, NLP can analyse data on the go with minimal human interference.
This system has limited functionality and can work on one specific task at a time. It does not recognise new domains or problems.
Lack of a coherent interface
NLP has no responsive interface which does not allow users to interact with the system properly.
It is neither completely reliable nor completely dependable. It’s possible to make errors in its projection and outcomes.
Difficulty in understanding ambiguity in Language
The system may not be able to give the correct response to the query consisting of ambiguous words or incorrectly constructed sentences.
Real-life Uses of NLP
Natural language processing has made its place in day-to-day activities. This branch of artificial intelligence stands crucial in terms of helping humans in innumerable ways by performing tasks that may otherwise be complicated to execute manually. Here are some examples of how NLP is used in our day to day lives:
Auto-complete & Auto-Correct
One of the most common examples of NLP are auto-complete and auto-correct which benefit every user to write error-free messages or content. Auto-complete is used by pioneers like Google to help searchers to ask concise and relevant questions.
Due to advancements in NLP, chatbots are being increasingly used to automate customer support. Some chatbots have advanced features that carry out tasks such as managing accounts, ordering products or services, and helping users navigate support articles and databases.
The search result is extensively used to show the results of search queries. When users type certain words in search bars, NLP processes them and shows the most relevant findings. According to think with Google “The entire process takes, in many cases, less than a tenth of a second � it’s practically instant.”
Amongst the best practices of NLP online is email filters which began with spam filters to unveil words or phrases that signalled spam messages. Like all other modifications of NLP, filters have also been upgraded.
Gmail classification is among the most dominant ones as it figures out if an email belongs to any of the three main categories: primary, social or promotions. It helps to keep the user inbox manageable.
Natural language processing ultimately strives to facilitate the intercourse between humans and machines using the software. It is important for a business because it breaks down the human language into chunks and makes it easier for machines to analyse it automatically.