Natural Language Processing in 2021: What’s in store?

LAST year, we saw a wave of digitisation in terms of growth in Artificial Intelligence, Internet of Things (IoT), Machine Learning and other such technologies to keep up with the changing dynamics of the industry. In 2021, we can foresee the greater impact of technology such as translators, chat-bots, and voice assistants to make our lives easier and improve the standard of living.

Among all of this, Natural Language Processing (NLP) – broadly defined as the automatic manipulation of natural language, like speech and text, by software – has shown some encouraging and path-breaking developments. Business leaders have started to invest more in it keeping in mind the umpteen benefits that are associated with it for the business sustenance.

NLP has helped in systematising the large amount of data that is generated every moment on social media, which is otherwise not possible to do manually. It has extended support in keeping track of customer’s thoughts and the kind of emotion, language and understanding they have towards the brand or product. This has helped product companies to quickly realise consumer behaviour and make relevant changes accordingly.

The approach is changing along with the advancements in technology and there is a scope of betterment that will ensure the smooth functioning of the company. The trends are dynamic and businesses need to adapt according to these trends. Similarly, NLP is seeing growth in the last few years and will definitely the next big thing in the industry.

Following are some of the areas where NLP can improve business for organisations in the coming years:

Advancements in chatbots and voice assistants

With an increase in the number of smart devices, there is a need to enhance the next generation chatbots and voice assistants. Even now, the programming is done in a systematic way, which gives them the liberty to answer a few general questions asked by the consumers. However, if a question that is not in the FAQ list is asked, it doesn’t have an answer. One can expect an improvement in the NLP tools with the help of desk software to give a better experience – like real-time responses – to the consumers, which will in turn help in customer retention.

NLP moving from research into production

This shift from NLP moving from research to production is something we can look forward to. This is because of the technological advancements in deep learning and transfer learning. This is also one of the major reasons behind increased investments in NLP across various industries. For example, in the healthcare industry, a lot has been done in terms of using NLP algorithms to extract accurate facts from genomic, pathology, lab and radiology reports. In order to make things simpler and lessen the burden on people associated with the healthcare industry, NLP is already being used to highlight high-risk solutions, fast drug recovery, diagnose patients and whatnot.

Holistic approach towards NLP

In order to achieve success and favourable results and to structure and scale an NLP project, it is very important to have a deep understanding of how AI works within a product from a business perspective. Without understanding the advantages of integrating AI and its effects on the job function of an organisation, no prediction model or e-discovery system will be successful. For NLP to be successful, organisations should completely understand other technologies associated with and implement them effectively so as to get the best outcome.

Deep Learning techniques in NLP models

Along with the advantages of NLP, there are a few shortcomings in the traditional machine learning-based NLP systems. Since these are time-based, it consumes a lot of time and often remains incomplete. These disadvantages can be overcome by using deep learning techniques in the NLP models.

Way Ahead

It is evident that there is a great scope of improvement in the NLP and looking at these trends in future, it is clear that NLP will be an integral part of businesses. Various leaders in the technology domain have already realised the benefits of NLP, while it will take time to adapt to these changes. Concisely, NLP will improve customer services; analyse the emotions/thought process of the users towards the brand, advance machine learning and artificial intelligence, which in turn will help to manage cost and decision-making for product companies.

By Savitha Chinnappareddy, Technical Lead

& Sandeep Naik, Technical Lead, Hi-Tec

QuEST Global

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