With the help of artificial intelligence, fields such as deep learning and machine learning are becoming a prudent reality. Such technologies are increasingly finding application in data analytics and helping leverage big data. At the same time, developers are integrating deep learning to program chatbots that can simulate human conversations with customers. Nevertheless, these next-gen platforms of machine learning are merely functional without the inventiveness of Natural Language Processing (NPL). Natural language processing (NLP) is an advanced language processing technology that enables human and machine communication. NLP embraces all the basic elements required for communication such as speech, text and voice recognition. In the coming years, machines are expected to do lot more than they are doing presently with applications such as NLP at the core. As per the latest report published by Market Research Future (MRFR), the global NLP Market is projected to surge at 24% CAGR during the assessment period (2017-2023).
Digitization has certainly made a mark on businesses and enterprises all over the world with the growing number of tech-savvy consumers finding new ways to interact on the web. The word community has been given a complete new meaning by social media while cryptocurrency is changing payment modules. Today, ecommerce exemplifies what could be called as convenience shopping and cloud computing has unrevealed the next level of data analytics to the masses. In all of this, NLP is playing and important combined with artificial intelligence and computational linguistics. Therefore, natural language processing is witnessing a widespread adoption across different verticals. However, a lot of miles are to be covered before NLP solutions truly reach their optimum capabilities. A greater precision, unambiguity, and structural efficiency with higher receptivity to enunciated commands is required. It is difficult to process human speech and is often ambiguous, depending on variables such as social context, pronunciations and regional dialects. Natural-language generation, natural-language processing and speech recognition are some of areas that developers continue to face challenges.
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Industry Trends and News
Massachusetts-based AI specialist Gamalon has recently completed a series A funding round worth $20 Mn, which was led Intel Capital. Omidyar Technology Ventures, Felicis Ventures, Rivas Capital, 406 Ventures, and Boston Seed Capital where the other participants.
Moscow-based content intelligence services providers ABBYY has recently launched an advanced text analytics for contracts. ABBYY’s platform will improvise a managed service that independently discover insights from contracts and lease to improve risk mitigation content migration and obligation analysis.
Natural Language Processing Market: Segmental Analysis
MRFR in its report has offered an exhaustive segmental analysis of the market based on type, deployment, technology, vertical, service and region. By type, the market has been segmented into hybrid, statistical and rule-based. By deployment, the market has been bifurcated into on-demand and on-premise. By technology the market has been segmented into text analytics, speech analytics, pattern & image recognition and auto-coding. By vertical, the market has been segmented into media & entertainment, retail sector and healthcare. By service the market has been segmented into maintenance, consulting and integration.
NLP Market – Regional Outlook
Based on region, North America is currently the most profitable market for natural language processing and is expected to remain highly lucrative throughout the assessment period. Presence of leading technology companies in the region is one of the major factor supporting the growth of the market in North America. The other two regions that are expected to remain crucial for the market’s expansion are Europe and Asia Pacific.
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NLP Market: Competitive Landscape
Some of the prominent market players mentioned in MRFR’s report include 3M Co. (U.S.), Apple Inc. (U.S.), Microsoft Corporation (U.S.), SAS Institute Inc. (U.S.), Verint Systems Inc. (U.S.), IBM Corporation (U.S.), Hewlett-Packard Co. (U.S.), Oracle Corporation (U.S.), Dolbey Systems Inc. (U.S.), and Net base Solutions Inc. (U.S.).
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