With growing computational capabilities, every kind of businesses are employing computers, smart phones and other similar devices to make their day-to-day operations simpler, quick and effective. Among the technologies that are creating some buzz in this direction include the natural language processing technologies. Natural language processing or simply NLP, in simpler terms refers to a part of artificial intelligence and linguistics that enables interactions between computers and natural languages of human beings. This technology has been into existence since early 1950s but till recently, it had and continues to be a subject of research and development. Many prominent breakthroughs have happened in terms of advancement of these technologies and have hence paved way for commercialization of this technology.
Language processing capabilities of computers have always been limited due to the presence of different dialects of the same language. Also, natural human language processing tools are still largely limited to particular set of languages especially those which were used by countries that were industrializing and felt the need for automation of processes and introduced machines that understood human language to carry out the processes. Moreover, natural language processing for many years now, has been a topic of research and development for researchers across the world and till now, commercial viability of the NLP technologies was very limited and many universities and language processing research bodies have spent years on development of natural language processing tools.
As a result of years of research efforts, NLP is now slowly being commercialized and companies like IBM has announced an investment of 1 billion USD into its “IBM Watson” and hopes to build it as a separate business unit. Other prominent companies like Nuance, 3M and HP have also joined the league and have dedicated NLP products. Other than these enterprises, NLP based specific solutions and tools are also being developed by several technology companies. For example, companies like Miia Technologies has developed NLP based HR solutions. Similarly, there are companies that develop solutions dedicated to healthcare, legal, media & publishing houses and other industries. All these developments point to the fact that natural language processing is rapidly being commercialized and moving forward, NLP based solutions will become more advanced and sophisticated supporting multiple languages and converting large amounts of data into an organized, structured and actionable data.
In a report titled “Global NLP Market 2014-2019” published by ResearchFox Consulting, an international market research company, the global natural language processing market was valued at USD 2.4 billion in 2014 and the market is expected to grow at a CAGR of 23.2% till 2019. According to this report, the main reasons that are attributed to the growth of NLP market include
- Information or data explosion, i.e., the big data growth where companies are faced with heaps of data but don’t know how this data can be best utilized within a limited time frame.
- Need for more structured data: It is believed that businesses that generate large amounts of data use only one third of this data to arrive at some inferences and the main reason for this being the lack of structured and organized data.
- Demand for text analytics and social media content analysis: With growth of internet, businesses want to know what their customers think about their brand and product and are thus analyzing customer feedback on the social media platform using text analytics and content analytics.
Apart from these, there are other region specific drivers, constraints, opportunities and challenges that have been mentioned and assessed in the report.
From the NLP provider point-of-view, the report provides information on the major NLP providers and their products in the market and from the demand side, the report sheds light on various aspects like the major industries that have been using these NLP products, the type of applications that are most preferred by them, the type of NLP solutions and their usage, type of end users (enterprise, mid-size and small business) that exist in the market and who are the major revenue generators.
The report also discusses explicitly about the major geographic regions that are prevalent in terms of NLP adoption and the regions that are expected to grow in the future.