Natural Language Generation (NLG) is a subdivision of Artificial Intelligence (AI) which is used to reduce the communication gaps between machines and humans. In very simple words, it acts as a translator which converts the computerized data into Natural Language representation. In one phrase we can say that "data in language out."

Natural Language Processing (NLP), is the term which sounds very similar to NLG. Generally, people misunderstand that both NLP and NLG are the same, but remember that these two terms are different. In fact, NLG is the part of NLP. Let's see how?

NLG is the type of NLP and sometimes referred as the Computational Linguistics (CL) and NLP encompasses all the software which generates human language, either in spoken or written form.

Majorly there are four type of NLP such as:

• Speech recognition to understand or note down the spoken language.

• Natural Language Understanding (NLU) to extracts information from written text.

• Natural Language Generation (NLG) produces narratives and reports in easy to read the language.

• Speech synthesis to speak and read out the text.

The applications of NLP combines the different aspects of it, for example, Apple's Siri and other intelligent personal assistants use speech to speech type of NLP.

Now, in this post, we discuss only NLG. So, let's move ahead and see how it works.

In the NLG conclusion or text is generated on the basis of collected data or input provided by the user. The process of generating the text can be simple, but in a sophisticated NLG system, it requires to include the stages of planning and merging the information generates text that looks natural and does not become repetitive.

One thing is clear that NLG has an amazing potential to make intelligent software applications. So, let's discuss the ways that NLG can simplify some of the complex tasks by transforming the machine representation into natural language.

Basically, there are two ways software applications use of NLG, either present a set of information to the users or automate the mass production of documents.

Converting tabular insights into narratives

Let's take an example of finance industry to understand this. For example, the analyst can easily understand the stock analysis report, equity reports, stress test report, etc. and make a better decision. In order to make users to understand the output, the software applications in the finance industry are using NLG to make the reports readable.

Numerical weather reports into text

The weather forecasting system frequently uses the NLG system to interpret the numerical value which is received as an input from supercomputers. For example, numerical prediction of wind speed, the intensity of perception, and other meteorological phenomena are recorded and to convert this data into the language form that users can understand they required NLG system required.

Now let's discuss the benefits of Natural Language Generation.

The benefits of NLG has very wide benefits but to utilize those benefits you need to adapt AI. Here we are listing some benefits of it for marketing and business management.

Automated content creation

NLG has the ability to create the organized structure of the data from the information processed in previous stages of NLP and NLU. By placing this well-structured data in a specific template, NLG can automate the process and supply the documentable form of data such as analytics report, product description, data-centric blog posts, and many more.

In this situation, the algorithms of machines have the complete library or we can say that they have the capability of creating the content in the desired form, the only thing that is left for the employees to promote that content to the target audiences via popular media channels. The NLG fulfills the two purposes of content developers and marketers.

The content generation depends on the ability of web mining and its APIs of the search engine to build effective content.

Significant reduction in human involvement

If you want to install the NLP system in your workplace then it becomes very important to hire data, literate professionals.

If you successfully implement the NLG system in your organization then you realize how expensive and ineffective employees are who spend hours in understanding the complex data. Legal documents, shareholder reports, press releases, and case studies will no longer require so much time.

Predictive inventory management

The success of inventory management for any store results in a great boost in terms of business goal and overall resultant profit given that certain products have very high margins. Data plays an important role in areas like supply chain, production rate, and sales analytics. With the help of this information store managers can make the decisions about maintaining inventory to its optimal levels.

When it comes to advanced NLG, it can work as an interactive medium for the data analysis and make the overall reporting process easy and informative. Instead of having to go through several charts and bars, graphs of data. store managers get clear narratives and analysis in desired format telling them whether they require specific item next week. With NLG managers have the best predictive model with clear guidance and recommendations on store performance and inventory management.

These are the benefits of NLG for organizations. Business owners can utilize the NLG system to reduce human errors and enhances their productivity.

If you want to harness the full potential of the NLG system then use this technology with mobile applications, it allows you to analyze your work potential. Techugo is the mobile application development company and expert in implementing the different technologies into the app. We provide you the dream application for your business which fills the gap between you and your success. So, if you have any concerns regarding application development, you can contact us.