Today, new technological advancements are coming into the field with full effect and companies are adopting the latest pieces of equipment to keep up with the new changes.
They are also focusing on implementing automation at various paces. One of the examples of advanced technology is Natural Language Processing or the NLP.
It is regarded as a component of intelligent automation, which enables computers to augment the productivity of people and automate knowledge work.
Computer vision, thinking and learning, and execution are the other components of NLP. Without further ado, let’s dive straight into this and learn more about NLP, intelligent automation, the benefits of NLP, and its technologies for intelligent automation.
What are Natural Language Processing and Intelligent Automation?
Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large volumes of natural language data.
In other words, it can also be referred to as the automatic manipulation of natural language, like speech and text, by software.
Intelligent Automation is the blend of artificial intelligence (AI) technologies and robotic process automation which jointly elevate immediate end-to-end business processes and enhance digital transformation.
Benefits of NLP
Now, let’s take a look at the benefits of Natural Language Processing-
Perform Large Scale Analysis-
This is one of the best advantages of NLP. NLP allows text analysis on all sorts of documents such as emails, social media data, etc.
It would process huge amounts of data that would normally take many days or weeks of manual analysis.
Accurate Analysis and Clear Objective-
With the help of NLP-powered tools, the tools can be trained to the language and the standards of your business.
So, once you have them on, they perform much more steadily and accurately than humans ever could. Also, when business evolves, you can tweak and continue to train your models.
This is very helpful, especially for bin picking, which makes the job faster.
Reduce Costs and Streamlines Processes-
NLP tools are at your service 24/7. The main advantage of NLP tools is that when you connect them to your data, you will be able to analyze your customer feedback on the go.
This enables you to gain information about customers if they are facing any problem with your service or product.
Improve Customer Satisfaction-
NLP tools allow you to properly analyze and sort customer service tickets by topic, urgency, etc and route them directly to the respective department or employee, making sure that the customer is not left unattended.
Empowers Employees-
Automating processes shapes save a lot of human labor hours. When utilizing data analysis to its full potential, your employee will be able to focus more on their personal work and tasks.
NLP Technologies that Helps Shape Intelligent Automation
Now let’s take a look at the applications of natural language processing that are being deployed today that help shape intelligent automation, as well as that, can help your business.
Chatbots and Cognitive Agents-
With the help of chatbots and cognitive agents, the need for a human agent is eliminated to some extent. Chatbots and cognitive assistants are mainly used to look up answers to your queries and lookup suitable information, or even schedule appointments.
There are two types of chatbots- simple and advanced, where simple chatbots only require a basic set of rules, whereas, advanced chatbots use deep learning to learn from conversations and improve themselves.
These chatbots are often mistaken for humans, it just shows how advanced they are.
Unstructured Information Management-
Unstructured information management (UIM) platforms eliminate the need for manual keyword search queries, which are regarded as very much time-consuming and error-prone.
Instead, UIM platforms are utilized to process large amounts of unstructured data and extract meaning from them.
Sentiment Analysis-
This is a technology that utilizes natural language processing to extract sentiments, preferably, such as approval or disapproval of a brand, from unstructured text such as tweets, for example.
Speech Analytics-
This is a component of NLP that merges UIM with sentiment analysis.
This type of technology is implemented mostly by call centers to turn transcriptions of phone conversations and text chats into structured data and interpret them using sentiment analysis.
Machine Translation-
Machine translation is regarded as an enormously powerful application of NLP.
Machine translation software is regarded as an enormously powerful application of NLP.
Currently, machine translation can provide you the gist of a web page or an email in a language you don’t speak, but they are not decisive enough to construct complete, thorough grammatical; and idiomatic translations.
Conclusion
At present, companies are trying their overall best to render their clients the best services they’ve got to offer such as mobile app development services, IoT services, etc.
Natural language processing (NLP) is still a huge help to businesses and companies, to automate processes and streamline decisions.
Author bio:
Feral Mohammed Hazem is an industry expert and a professional writer working at ThinkPalm Technologies, a software and mobile app development services provider.
He has a keen interest in AI. He is fascinated by futuristic technology and its ways. Off the screen, he is a movie buff, likes playing basketball and listening to music.
