— Natural Language Processing Industry 2019
The global natural language processing is expected to develop at a CAGR of 15.7% during the forecast time frame. Natural language processing (NATURAL LANGUAGE PROCESSING) is a component of artificial intelligence and it enables computers to connect with humans in their own language. For instance, natural language processing makes it workable for computers to hear speech, read text, measure sentiment, interpret it, and decide which portions are significant.
The primary focus of natural language processing is to limit the time taken to comprehend computer languages, such as Java, C, C++, and some more. Natural language processing is likewise used in big data analytics, because of the fact that enormous measures of data are being produced from sources like web blogs audio, social networking sites, emails, documents, and forums.
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The significant players working in the global natural language processing are IBM Incorporation, 3M, Google, Microsoft Corporation, HPE, Apple Incorporation, Verint Systems, Dolbey Systems, SAS Institute Inc. furthermore, NetBase Solutions. These players have ventured up new product innovations and new product launches, so as to acquire attention from the customers. Additionally, the development of the market is ascribed to geographical expansion, strategic mergers and acquisitions and joint ventures and partnerships, so as to ensure long-term sustenance in the market.
The natural language processing report gives analysis to the period from 2016 to 2026, where 2019 to 2026 is the forecast time frame with 2018 as the base year. This report on natural language processing covers a top to bottom analysis of the market including statistical and subjective data points, along with the key market drivers and opportunities and restraints that have positive or negative effects on the general global market.
An exclusive coverage has been accommodated market drivers and challenges and opportunities for a country-level market in the respective regional segments. The report comprises a competitive analysis of the key players functioning in the market and covers top to bottom data identified with the competitive landscape of the market and the recent strategies and products that will help or affect the market in the coming years.
The global natural language processing market has been sectioned based on deployment, technology, type, application, and end-use. Based on deployment, the market has been divided into on-premise and cloud. The cloud section is additionally classified into public cloud, private cloud, and hybrid cloud. Based on technology, the market has been divided into optical character recognition (OCR), speech analytics, interactive voice response (IVR), image recognition, and others.
The type fragment is additionally classified into statistical natural language processing, rule-based natural language processing, and hybrid natural language processing. Based on applications, the market can be classified into report generation, information extraction, machine translation, and others. Based on end-use, the natural language processing market can be sectioned into automotive, retail and consumer goods, healthcare, banking, financial services and insurance, government, and others.
The optical character recognition portion is expected to hold the biggest market portion of natural language processing in the coming years
Recognition technologies are the most broadly used technologies in natural language processing. Greatest companies, from huge to little ventures use certain types of recognition technology like interactive voice recognition, optical character recognition, or image recognition. Recognition technology is basically used for machine translation and information extraction.
The speech analytics section is expected to observe the quickest development during the forecast time frame
Speech analytics enables users to settle on genuine business decisions by giving quicker and inside and out investigations of voice data. Speech analytics is increasing colossal importance among different ventures across the world, since the old-style text-based analytics used by companies can't deal with complex business issues.
A few undertakings are utilizing speech analytics to make driving edge analytics solutions in order to increase a superior comprehension of customer necessities. The on-premise speech analytics is for the most part favored by organizations. This is because of the fact that organizations with complicated IT structures that require a high measure of integration with different applications, settle on the on-premise speech analytics. For instance, deals support, CRM, marketing, and other technical help devices by and large support the on-premise model to mitigate compatibility issues.
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Table Of Contents – Major Key Points
Chapter 1 OVERVIEW AND SCOPE
Chapter 2 Executive Summary
Chapter 3 Market Insights
Chapter 4 Industry Trends
Chapter 5 Global Natural Language Processing Market, by Deployment
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