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Natural Language Processing Market Report

RA05343

Natural Language Processing Market by Component (Solution and Services), Deployment Type (Cloud and On-premise Model), Type (Rule Based, Statistical, and Hybrid), Application Type (Machine Translation, Automatic Summarization, Sentiment Analysis, Text Classification, Question Answering, and Others), Vertical Type (Automotive, BFSI, Government, Healthcare, Media & Entertainment, Retail & Consumer Goods, and Others), and Regional Analysis: Global Opportunity Analysis and Industry Forecast, 2020–2027
Update Available On-Demand

RA05343

Pages: 353

Apr 2021

COVID-19

pandemic has shown to have an enormous impact on most
industries.

Click Here to access our comprehensive analysis of the

Impact of covid-19 on Natural Language Processing Market

Natural Language Processing Market Analysis

The global natural language processing market was valued at $9,701.56 million in 2019, and is projected to reach $42,389.83 million by 2027, at a CAGR of 20.6%. 

Market Synopsis

The adoption of natural language processing is rapidly increasing along with the increase in demand for big data, data analytics, powerful computing, and enhanced algorithms.

Complexities due to the usage of code-mixed language while implementing natural language processing solutions is hindering the market growth.

North America was the highest revenue contributor, accounting for $3,669.1 million in 2019, and is estimated to grow with a CAGR of 19.5%.

Natural Language Processing Overview

Natural language processing is a sub-field of linguistics, computer science, and artificial intelligence that is concerned with the interactions between computers and human language that results in computers processing and analyzing large amounts of natural language data.

Impact Analysis of COVID-19 on the Global Natural Language Processing Market

The natural language processing market has witnessed a severe impact in 2020 due to the outbreak of the coronavirus pandemic. The pandemic increased the rate of attrition and affected almost every industry. The lockdown had a negative impact on the global manufacturing units and the supply chains as the continuity of operations of all the verticals was severely disrupted. The sectors or verticals facing the maximum impact are manufacturing, transportation, retail, supply chain and logistics and consumer goods. The availability of essential goods was impacted due to the lockdown regulations and also due to the lack of manpower. However, it is expected that by the end of 2021, the situation might come under control as the demand for natural language processing solutions and services is increasing due to the increased demand for enhancing customers experiences in various industries such as healthcare.  To enable digital transformation initiatives several sectors are already planning to deploy a diverse array of natural language processing solutions and services. These initiatives will improve operations and enhance customer viewing experience. The reduction in operational costs, better customer experiences, improved customer rate of attrition, enhanced visibility into processes and operations, improved real-time decision-making are key business, and operational priorities are expected to drive the adoption of NLP.

Rising Need for Enhanced Customer Experience to be an Important Factor for the Growth of the Market

It is important and necessary to understand the customers feedbacks and requirements which is becoming very difficult in the present scenario, because of the increasing number of channels through which the clients provide their requirement or feedback. In order to understand these requirements and feedbacks related to products or services and companies are constantly looking for an opportunity to understand and enhance customer experience capabilities. Artificial intelligence and natural language processing assist companies in analyzing the customer inquiry or feedbacks and is further converted them into individual solutions. These factors are anticipated to drive the market growth over the projected time frame. 

To know more about global application security market drivers, get in touch with our analysts here.

Complexities due to the Usage of Code-Mixed Language is a Restraining Factor

Code-Mixed (CM) language is the alteration of languages within a conversation and is a common communicative phenomenon that occurs in multilingual communities across the world.  CM language has been associated with informal or casual speech. There is evidence that the CM language has become the default code of communication in several societies, such as urban India and Mexico. CM also has pervaded written text, especially in computer-mediated communication and social media. NLP processes such as normalization, language identification, language modeling, part-of-speech tagging, dependency parsing, machine translation, and Automatic Speech Recognition (ASR) face issues while working on non-canonical multilingual data as two or more languages are mixed. The processes of NLP are restrained due to the presence of various codes and languages. 

Increase in Investments in Healthcare Sector are Generating Major Opportunities in the Natural Processing Language Market

The healthcare sub-segment is generating a large amount of data nowadays, with an increased pace of digitalization among hospitals and other healthcare premises. Healthcare organizations are working on enormous amount of useful data with the analytics-driven approach. However, such organizations are finding it difficult without a sophisticated systems as it is challenging to analyze the text data. As a consequence, NLP has appeared as an important technology to extract meaningful insights from large volumes of data. The consequent demand for effective data management and advanced data analytics has also seen a significant rise in the healthcare industry over the last ten years. Moreover, it is expected that there will be a huge scope of opportunities for NLP technologies in the healthcare industry in the next five years. Personal Health Records (PHRs) are becoming widely accepted and new initiatives have been taken to make it easier to download and share medical records with different medical and insurance providers. For instance, NLP systems could extract any notes in a patient's electronic record that mention prescribed medications and if they were effective. It is expected that this market will further flourish with the growing trend of superior data management and analytics of mobile apps.

Natural Language Processing Market, by Component

On the basis of component, natural language processing is divided into solutions and services.

Natural Language Processing Market, by Component

Source: Research Dive Analysis

The solution sub-segment was the highest contributor to the market, with $5,048.3 million in 2019, and is estimated to grow at a CAGR of 19.1% during the forecast period. The demand for NLP software tools and platforms is increasing globally due to the rising demand to gain real-time insights from voice or speech data across different verticals.

Natural Language Processing Market, by Deployment

On the basis of deployment, natural language processing is divided into cloud and on-premise model.

Natural Language Processing Market, by Deployment

Source: Research Dive Analysis

The on-premises sub-segment was the highest contributor to the market, with $5,327.9 million in 2019, and is estimated to grow at a CAGR of 18.2% during the forecast period. Additionally, cloud sub segment is anticipated to grow at a highest CAGR, as cloud-based natural language processing platform enables users to utilize and analyze multilingual content, user-generated content, and other web-content in a more secure manner and can access this data from anywhere in the world.                                                                                            

Natural Language Processing Market, by Type

On the basis of type, natural language processing is segmented into rule based, statistical, and hybrid.

Natural Language Processing Market, by Type

Source: Research Dive Analysis

The statistical sub-segment was the highest contributor to the market, with $3,701.6 million in 2019, and is estimated to grow at a CAGR of 19.1% during the forecast period. Statistical natural language processing (NLP) intends to perform statistical inference for the field of natural language processing. Statistical NLP also enables natural conversations between chat-bots and humans.

Natural Language Processing Market, by Application Type

On the basis of application type, natural language processing is segmented into machine translation, automatic summarization, sentiment analysis, text classification, question answering, and others.

Natural Language Processing Market, by Application Type

Source: Research Dive Analysis

The machine translation (MT) sub-segment was the highest contributor to the market, with $2,394.3 million in 2019, and is expected to grow at a CAGR of 19.0% during the upcoming period. One of the key factor driving the MT sub-segment is this system enables you to save your time while translating large texts. This advantage of machine translation is increasing the sub-segment growth.

Natural Language Processing Market, by Vertical Type

On the basis of application type, natural language processing is segmented into automotive, BFSI, government, healthcare, media & entertainment, retail & consumer goods, and others.

Natural Language Processing Market, by Vertical Type

Source: Research Dive Analysis

The media and entertainment sub-segment was the highest contributor to the market, with $1,931.1 million in 2019, and is expected to grow at a CAGR of 19.1% during the forecast period. The rising adoption of digital platforms in entertainment has been transforming how media companies around the world operate and advertise to reach their audience. There is a dire need for adding personalization and delivering value to meet the rising customer expectations and demands. Several companies in the media and entertainment sector are turning to artificial intelligence (AI) technologies to deliver great customer experiences at a large scale.                                               

Natural Language Processing Market, by Region Type

The natural language processing market was investigated across North America, Europe, Asia-Pacific, and LAMEA regions.

Natural Language Processing Market, by Region Type

Source: Research Dive Analysis

Investment Opportunities by Start-ups is Increasing the Market Share in North America

North America was the highest revenue contributor, accounting for $3,669.1 million in 2019, and is expected to experience the highest CAGR of 19.5%. The organizations in North America are investing in the advancements of NLP and its applications. With the increasing unstructured data produced by many start-ups in the U.S. are gradually deploying natural language processing services. Furthermore, many start-up companies are entering in the NLP market in the countries like U.S. This is due to increasing demand for AI and NLP enabled products and solutions that are present in the market.

Increasing Investments in Artificial Intelligence are Driving the Market Growth in Asia-Pacific Region

Asia-Pacific region is expected to grow at the highest CAGR of 21.1% during the forecast period from $2039.30 million in 2019 on the account of rising awareness and increasing investments in artificial intelligence. Increasing investment in AI by Chinese players such as Baidu and Alibaba are contributing significantly towards the revenue growth. Moreover, the increasing adoption of the smart devices in this region is also driving the growth of the market.

Competitive Scenario of Global Natural Language Processing Market

Product launches and mergers & acquisitions are common strategies followed by major market players.
Competitive Scenario of Global Natural Language Processing Market

Source: Research Dive Analysis

Some of the leading NLP market players IBM, Microsoft, Google, Amazon, Facebook, Apple Inc., 3M, Intel, Baidu, Inc. SAS Institute Inc. Established as well as start-up organizations operating in the natural language processing industry are focusing majorly on advanced technological developments, mergers & acquisitions, business expansion, and others.

Porter’s Five Forces Analysis for Natural Language Processing Market:

  • Bargaining Power of Suppliers: The suppliers of the global natural language processing industry are less in number.
    Hence, the bargaining power of the supplier is high.
  • Bargaining Power of Buyer: The natural language processing market is fragmented. Hence, there is a vast product differentiation found in the natural language processing solution. Thus, the bargaining power of the buyer is low.
  • Threat of New Entrants: Emerging companies are following various strategies such as product innovation, combined with strategic collaboration to strengthen their footprint in the international market.
    Hence, the threat of the new entrant is high.
  • Threat of Substitutes: There is no alternative product for natural language processing solutions.
    Thus, the threat of substitutes is low.
  • Competitive Rivalry in the Market: Strong presence of innovation leaders including Google, Microsoft are creating huge rivalry in the global industry. Heavy investment in R&D coupled with major business expansion are some of the factors increasing competitive rivalry among the key players.
    Hence, competitive rivalry in the market is high. 

Aspect

Particulars

  Historical Market Estimations

  2018-2019

  Base Year for Market Estimation

  2019

  Forecast timeline for Market Projection

  2020-2027

  Geographical Scope

  North America, Europe, Asia-Pacific, LAMEA

  Segmentation by Component

  • Solution
  • Services

  Segmentation by Deployment Mode

  • On-Premise
  • Cloud

  Segmentation by Type

  • Rule based
  • Statistical
  • Hybrid

  Segmentation by Application

  • Machine Translation
  • Automatic Summarization
  • Sentiment Analysis
  • Text Classification
  • Question Answering
  • Others

  Segmentation by Vertical

  • Automotive
  • BFSI
  • Government
  • Healthcare
  • Media and Entertainment
  • Retail and Consumer Goods
  • Others

  Key Countries Covered

The U.S.,Canada, Mexico, Germany, FranceUK, Italy, Spain, Rest of Europe, China, Australia, Japan, India, South Korea, Rest of Asia-Pacific, Latin America, Middle East, and Africa

  Key Companies Profiled

  • IBM
  • Microsoft
  • Google
  • Amazon
  • Facebook
  • Apple Inc.
  • 3M
  • Intel
  • Baidu, Inc.
  • SAS Institute Inc.

Frequently Asked Questions
 

A. The global natural language processing market size was over $9,701.6 million in 2019 and is projected to reach $41,695.1 million by 2027.

A. Google Inc and Microsoft Corporation are some of the key players in the global natural language processing market.

A. The Asia-Pacific region possesses great investment opportunities for investors to witness the most promising growth in the future.

A. Asia-Pacific natural language processing market is anticipated to grow at 21.1% CAGR during the forecast period.

A. Technological development and strategic partnerships are the key strategies opted by the operating companies in this market.

A. IBM Corporation and Google Inc companies are investing more on R&D activities for developing new products and technologies.

1.Research Methodology

1.1.Desk Research
1.2.Real time insights and validation
1.3.Forecast model

1.4.Assumptions and forecast parameters

1.4.1.Assumptions
1.4.2.Forecast parameters

1.5.Data sources

1.5.1.Primary
1.5.2.Secondary

2.Executive Summary

2.1.360° summary
2.2.By component trends
2.3.By deployment mode trends
2.4.By type trends

2.5.By application trends
2.6.By vertical trends

3.Market overview

3.1.Market segmentation & definitions
3.2.Key takeaways

3.2.1.Top investment pockets
3.2.2.Top winning strategies

3.3.Porter’s five forces analysis

3.3.1.Bargaining power of consumers
3.3.2.Bargaining power of suppliers
3.3.3.Threat of new entrants
3.3.4.Threat of substitutes
3.3.5.Competitive rivalry in the market

3.4.Market dynamics

3.4.1.Drivers
3.4.2.Restraints
3.4.3.Opportunities

3.5.Technology landscape
3.6.Regulatory landscape
3.7.Patent landscape
3.8.Market value chain analysis

3.8.1.Stress point analysis
3.8.2.Raw material analysis
3.8.3.Manufacturing process
3.8.4.Distribution channel analysis
3.8.5.Operating vendors

3.8.5.1.Raw material suppliers
3.8.5.2.Product manufacturers
3.8.5.3.Product distributors

3.9.Strategic overview

4.Natural Language Processing Market, by Component

4.1.Solution

4.1.1.Market size and forecast, by region, 2019-2027
4.1.2.Comparative market share analysis, 2019 & 2027

4.2.Services

4.2.1.Market size and forecast, by region, 2019-2027
4.2.2.Comparative market share analysis, 2019 & 2027

5.Natural Language Processing Market, by Deployment Mode

5.1.On-Premise

5.1.1.Market size and forecast, by region, 2019-2027
5.1.2.Comparative market share analysis, 2019 & 2027

5.2.Cloud

5.2.1.Market size and forecast, by region, 2019-2027
5.2.2.Comparative market share analysis, 2019 & 2027

6.Natural Language Processing Market, by Type

6.1.Rule Based

6.1.1.Market size and forecast, by region, 2019-2027
6.1.2.Comparative market share analysis, 2019 & 2027

6.2.Statistical

6.2.1.Market size and forecast, by region, 2019-2027
6.2.2.Comparative market share analysis, 2019 & 2027

6.3.Hybrid

6.3.1.Market size and forecast, by region, 2019-2027
6.3.2.Comparative market share analysis, 2019 & 2027

7.Natural Language Processing Market, by Application

7.1.Machine Translation

7.1.1.Market size and forecast, by region, 2019-2027
7.1.2.Comparative market share analysis, 2019 & 2027

7.2.Automatic Summarization

7.2.1.Market size and forecast, by region, 2019-2027
7.2.2.Comparative market share analysis, 2019 & 2027

7.3.Sentiment Analysis

7.3.1.Market size and forecast, by region, 2019-2027
7.3.2.Comparative market share analysis, 2019 & 2027

7.4.Text Classification

7.4.1.Market size and forecast, by region, 2019-2027
7.4.2.Comparative market share analysis, 2019 & 2027

7.5.Question Answering

7.5.1.Market size and forecast, by region, 2019-2027
7.5.2.Comparative market share analysis, 2019 & 2027

7.6.Others

7.6.1.Market size and forecast, by region, 2019-2027
7.6.2.Comparative market share analysis, 2019 & 2027

8.Natural Language Processing Market, by Vertical

8.1.Automotive

8.1.1.Market size and forecast, by region, 2019-2027
8.1.2.Comparative market share analysis, 2019 & 2027

8.2.BFSI

8.2.1.Market size and forecast, by region, 2019-2027
8.2.2.Comparative market share analysis, 2019 & 2027

8.3.Government

8.3.1.Market size and forecast, by region, 2019-2027
8.3.2.Comparative market share analysis, 2019 & 2027

8.4.Media and Entertainment 

8.4.1.Market size and forecast, by region, 2019-2027
8.4.2.Comparative market share analysis, 2019 & 2027

8.5.Consumer Goods

8.5.1.Market size and forecast, by region, 2019-2027
8.5.2.Comparative market share analysis, 2019 & 2027

8.6.Others

8.6.1.Market size and forecast, by region, 2019-2027
8.6.2.Comparative market share analysis, 2019 & 2027

9.Natural Language Processing Market, by Region

9.1.North America

9.1.1.Market size and forecast, by component, 2019-2027
9.1.2.Market size and forecast, by deployment mode, 2019-2027
9.1.3.Market size and forecast, by type, 2019-2027
9.1.4.Market size and forecast, by application, 2019-2027
9.1.5.Market size and forecast, by vertical, 2019-2027
9.1.6.Market size and forecast, by country, 2019-2027
9.1.7.Comparative market share analysis, 2019 & 2027

9.1.8.U.S.

9.1.8.1.Market size and forecast, by component, 2019-2027
9.1.8.2.Market size and forecast, by deployment mode, 2019-2027
9.1.8.3.Market size and forecast, by type, 2019-2027
9.1.8.4.Market size and forecast, by application, 2019-2027
9.1.8.5.Market size and forecast, by vertical, 2019-2027
9.1.8.6.Comparative market share analysis, 2019 & 2027

9.1.9.Canada

9.1.9.1.Market size and forecast, by component, 2019-2027
9.1.9.2.Market size and forecast, by deployment mode, 2019-2027
9.1.9.3.Market size and forecast, by type, 2019-2027
9.1.9.4.Market size and forecast, by application, 2019-2027
9.1.9.5.Market size and forecast, by vertical, 2019-2027
9.1.9.6.Comparative market share analysis, 2019 & 2027

9.1.10.Mexico

9.1.10.1.Market size and forecast, by component, 2019-2027
9.1.10.2.Market size and forecast, by deployment mode, 2019-2027
9.1.10.3.Market size and forecast, by type, 2019-2027
9.1.10.4.Market size and forecast, by application, 2019-2027
9.1.10.5.Market size and forecast, by vertical, 2019-2027
9.1.10.6.Comparative market share analysis, 2019 & 2027

9.2.Europe

9.2.1.Market size and forecast, by component, 2019-2027
9.2.2.Market size and forecast, by deployment mode, 2019-2027
9.2.3.Market size and forecast, by type, 2019-2027
9.2.4.Market size and forecast, by application, 2019-2027
9.2.5.Market size and forecast, by vertical, 2019-2027
9.2.6.Market size and forecast, by country, 2019-2027
9.2.7.Comparative market share analysis, 2019 & 2027

9.2.8.Germany 

9.2.8.1.Market size and forecast, by component, 2019-2027
9.2.8.2.Market size and forecast, by deployment mode, 2019-2027
9.2.8.3.Market size and forecast, by type, 2019-2027
9.2.8.4.Market size and forecast, by application, 2019-2027
9.2.8.5.Market size and forecast, by vertical, 2019-2027
9.2.8.6.Comparative market share analysis, 2019 & 2027

9.2.9.UK

9.2.9.1.Market size and forecast, by component, 2019-2027
9.2.9.2.Market size and forecast, by deployment mode, 2019-2027
9.2.9.3.Market size and forecast, by type, 2019-2027
9.2.9.4.Market size and forecast, by application, 2019-2027
9.2.9.5.Market size and forecast, by vertical, 2019-2027
9.2.9.6.Comparative market share analysis, 2019 & 2027

9.2.10.France

9.2.10.1.Market size and forecast, by component, 2019-2027
9.2.10.2.Market size and forecast, by deployment mode, 2019-2027
9.2.10.3.Market size and forecast, by type, 2019-2027
9.2.10.4.Market size and forecast, by application, 2019-2027
9.2.10.5.Market size and forecast, by vertical, 2019-2027
9.2.10.6.Comparative market share analysis, 2019 & 2027

9.2.11.Spain

9.2.11.1.Market size and forecast, by component, 2019-2027
9.2.11.2.Market size and forecast, by deployment mode, 2019-2027
9.2.11.3.Market size and forecast, by type, 2019-2027
9.2.11.4.Market size and forecast, by application, 2019-2027
9.2.11.5.Market size and forecast, by vertical, 2019-2027
9.2.11.6.Comparative market share analysis, 2019 & 2027

9.2.12.Italy 

9.2.12.1.Market size and forecast, by component, 2019-2027
9.2.12.2.Market size and forecast, by deployment mode, 2019-2027
9.2.12.3.Market size and forecast, by type, 2019-2027
9.2.12.4.Market size and forecast, by application, 2019-2027
9.2.12.5.Market size and forecast, by vertical, 2019-2027
9.2.12.6.Comparative market share analysis, 2019 & 2027

9.2.13.Rest of Europe

9.2.13.1.Market size and forecast, by component, 2019-2027
9.2.13.2.Market size and forecast, by deployment mode, 2019-2027
9.2.13.3.Market size and forecast, by type, 2019-2027
9.2.13.4.Market size and forecast, by application, 2019-2027
9.2.13.5.Market size and forecast, by vertical, 2019-2027
9.2.13.6.Comparative market share analysis, 2019 & 2027

9.3.Asia Pacific

9.3.1.Market size and forecast, by component, 2019-2027
9.3.2.Market size and forecast, by deployment mode, 2019-2027
9.3.3.Market size and forecast, by type, 2019-2027
9.3.4.Market size and forecast, by application, 2019-2027
9.3.5.Market size and forecast, by vertical, 2019-2027
9.3.6.Market size and forecast, by country, 2019-2027
9.3.7.Comparative market share analysis, 2019 & 2027

9.3.8.China

9.3.8.1.Market size and forecast, by component, 2019-2027
9.3.8.2.Market size and forecast, by deployment mode, 2019-2027
9.3.8.3.Market size and forecast, by type, 2019-2027
9.3.8.4.Market size and forecast, by application, 2019-2027
9.3.8.5.Market size and forecast, by vertical, 2019-2027
9.3.8.6.Comparative market share analysis, 2019 & 2027

9.3.9.India 

9.3.9.1.Market size and forecast, by component, 2019-2027
9.3.9.2.Market size and forecast, by deployment mode, 2019-2027
9.3.9.3.Market size and forecast, by type, 2019-2027
9.3.9.4.Market size and forecast, by application, 2019-2027
9.3.9.5.Market size and forecast, by vertical, 2019-2027
9.3.9.6.Comparative market share analysis, 2019 & 2027

9.3.10.Japan

9.3.10.1.Market size and forecast, by component, 2019-2027
9.3.10.2.Market size and forecast, by deployment mode, 2019-2027
9.3.10.3.Market size and forecast, by type, 2019-2027
9.3.10.4.Market size and forecast, by application, 2019-2027
9.3.10.5.Market size and forecast, by vertical, 2019-2027
9.3.10.6.Comparative market share analysis, 2019 & 2027

9.3.11.Australia

9.3.11.1.Market size and forecast, by component, 2019-2027
9.3.11.2.Market size and forecast, by deployment mode, 2019-2027
9.3.11.3.Market size and forecast, by type, 2019-2027
9.3.11.4.Market size and forecast, by application, 2019-2027
9.3.11.5.Market size and forecast, by vertical, 2019-2027
9.3.11.6.Comparative market share analysis, 2019 & 2027

9.3.12.South Korea

9.3.12.1.Market size and forecast, by component, 2019-2027
9.3.12.2.Market size and forecast, by deployment mode, 2019-2027
9.3.12.3.Market size and forecast, by type, 2019-2027
9.3.12.4.Market size and forecast, by application, 2019-2027
9.3.12.5.Market size and forecast, by vertical, 2019-2027
9.3.12.6.Comparative market share analysis, 2019 & 2027

9.3.13.Rest of Asia Pacific

9.3.13.1.Market size and forecast, by component, 2019-2027
9.3.13.2.Market size and forecast, by deployment mode, 2019-2027
9.3.13.3.Market size and forecast, by type, 2019-2027
9.3.13.4.Market size and forecast, by application, 2019-2027
9.3.13.5.Market size and forecast, by vertical, 2019-2027
9.3.13.6.Comparative market share analysis, 2019 & 2027

9.4.LAMEA

9.4.1.Market size and forecast, by component, 2019-2027
9.4.2.Market size and forecast, by deployment mode, 2019-2027
9.4.3.Market size and forecast, by type, 2019-2027
9.4.4.Market size and forecast, by application, 2019-2027
9.4.5.Market size and forecast, by vertical, 2019-2027
9.4.6.Market size and forecast, by country, 2019-2027
9.4.7.Comparative market share analysis, 2019 & 2027

9.4.8.Latin America  

9.4.8.1.Market size and forecast, by component, 2019-2027
9.4.8.2.Market size and forecast, by deployment mode, 2019-2027
9.4.8.3.Market size and forecast, by type, 2019-2027
9.4.8.4.Market size and forecast, by application, 2019-2027
9.4.8.5.Market size and forecast, by vertical, 2019-2027
9.4.8.6.Comparative market share analysis, 2019 & 2027

9.4.9.Middle East 

9.4.9.1.Market size and forecast, by component, 2019-2027
9.4.9.2.Market size and forecast, by deployment mode, 2019-2027
9.4.9.3.Market size and forecast, by type, 2019-2027
9.4.9.4.Market size and forecast, by application, 2019-2027
9.4.9.5.Market size and forecast, by vertical, 2019-2027
9.4.9.6.Comparative market share analysis, 2019 & 2027

9.4.10.Africa

9.4.10.1.Market size and forecast, by component, 2019-2027
9.4.10.2.Market size and forecast, by deployment mode, 2019-2027
9.4.10.3.Market size and forecast, by type, 2019-2027
9.4.10.4.Market size and forecast, by application, 2019-2027
9.4.10.5.Market size and forecast, by vertical, 2019-2027
9.4.10.6.Comparative market share analysis, 2019 & 2027

10.Company profiles

10.1.IBM

10.1.1.Business overview
10.1.2.Financial performance
10.1.3.Product portfolio
10.1.4.Recent strategic moves & developments
10.1.5.SWOT analysis

10.2.Microsoft

10.2.1.Business overview
10.2.2.Financial performance
10.2.3.Product portfolio
10.2.4.Recent strategic moves & developments
10.2.5.SWOT analysis

10.3.Google. Inc

10.3.1.Business overview
10.3.2.Financial performance
10.3.3.Product portfolio
10.3.4.Recent strategic moves & developments
10.3.5.SWOT analysis

10.4.Amazon

10.4.1.Business overview
10.4.2.Financial performance
10.4.3.Product portfolio
10.4.4.Recent strategic moves & developments
10.4.5.SWOT analysis

10.5.Facebook

10.5.1.Business overview
10.5.2.Financial performance
10.5.3.Product portfolio
10.5.4.Recent strategic moves & developments
10.5.5.SWOT analysis

10.6.Apple

10.6.1.Business overview
10.6.2.Financial performance
10.6.3.Product portfolio
10.6.4.Recent strategic moves & developments
10.6.5.SWOT analysis

10.7.3M

10.7.1.Business overview
10.7.2.Financial performance
10.7.3.Product portfolio
10.7.4.Recent strategic moves & developments
10.7.5.SWOT analysis

10.8.Intel

10.8.1.Business overview
10.8.2.Financial performance
10.8.3.Product portfolio
10.8.4.Recent strategic moves & developments
10.8.5.SWOT analysis

10.9.Baidu

10.9.1.Business overview
10.9.2.Financial performance
10.9.3.Product portfolio
10.9.4.Recent strategic moves & developments
10.9.5.SWOT analysis

10.10.SAS

10.10.1.Business overview
10.10.2.Financial performance
10.10.3.Product portfolio
10.10.4.Recent strategic moves & developments
10.10.5.SWOT analysis

In the recent years, the field of natural language processing (NLP) has gained a lot of traction and is one of the most dominant areas in data science. NLP is a subfield of artificial intelligence (AI) which aids machines in processing and understanding the human language in any given context so that they can automatically perform repetitive tasks like summarization, machine translation, ticket classification, and many others. Along with various innovations from giant companies like Google, NLP has witnessed progression in precision, speed, and even methods that are relied on by computer scientists to resolve complex problems.

With the invention of AI bots such as Alexa, Cortana, Siri, and Google Assistant the use of NLP has surged many folds. Scientists are currently focused on building models that can better comprehend human languages such as English, Hindi, Mandarin, Japanese, Spanish, etc. which are formally known as natural languages. Here are some trends projected to dominate in the natural language processing sectors in the upcoming years:

  • With growing innovations in the field of AI, machine learning is expected to play a vital role in the natural language processing techniques, particularly in text analytics. In the future years, machine learning engine can be used to perform more thorough analysis by means of supervised and unsupervised learning.
  • The continuous evolution of social media platforms clearly indicated that these platforms are going to take over an even more significant role in how companies make decisions. For example, at the time of a quarterly report, a company can depend on several NLP tools to monitor the customer reviews, feedbacks, and responses about their company on social media platforms and in the news. 
  • The rising pragmatic use of NLP can allow companies with large quantities of unstructured text or spoken data to tackle dark data problems and efficiently identify and collate them for insights. 
  • NLP is also expected to become more common in areas that need to understand user intent such as intelligent chatbots and semantic search. Along with the growing use of deep learning as well as unsupervised and supervised machine learning, the plethora of natural language technologies are expected to endure to mold the communication capacity of cognitive computing.
  • NLP is likely to play a vital part in tracking and monitoring market intelligence reports to mine intelligent data for companies for forming upcoming strategies. From 2021, NLP is predicted to find applications in a wide range of business areas. Presently, this technology is extensively used in financial marketing. It is helpful in sharing comprehensive insights into tender delays, market views, and closings and extracting information from large data sources.

Recent Developments in the Natural Language Processing Arena

The adoption of natural language processing is rapidly growing owing to rising demand for big data, data analytics, powerful computing, and enhanced algorithms. Several players in the natural language processing market are profoundly investing in various developments related to natural language processing.

For instance:

  • In July 2019, Facebook AI and researchers from the University of Washington formulated methods to improve Google’s BERT language model and attain performance on par or beyond state-of-the-art results in SQuAD, GLUE, and RACE benchmark data sets.
  • In April 2020, researchers from the Stanford University NLP have built Stanza, a multi-human language tool kit. This is tool kit is useful for those working with text from many locales—for instance, social media. It offers support for operating numerous precise natural language processing tools on 60+ languages and for retrieving the Java Stanford CoreNLP software from Python.
  • In April 2020, researchers from Microsoft Research and Google AI have introduced new benchmarks for cross-language natural-language understanding (NLU) tasks for AI systems like named-entity recognition and question answering systems. Google's XTREME covers 40 languages and consists of 9 tasks, whereas Microsoft's XGLUE covers 27 languages and 11 tasks.

Impact of COVID-19 on the Natural Language Processing Market

The abrupt rise of COVID-19 pandemic has made a severe impact on the growth of the global natural language processing market. As per a report by Research Dive, the global natural language processing market is estimated to garner $42,389.83 million, growing at a CAGR of 20.6% from 2020 to 2027. As the pandemic situation is relaxing, the demand for natural language processing solutions and services is growing owing to the surging need for enhanced customers experiences in several industries such as healthcare. Moreover, to facilitate digital transformation in work processes, several industries are already planning to implement a varied range of natural language processing solutions and services. Moreover, NLP is going to be one of the dominating technologies in Artificial Intelligence in the near future. All these factors are likely to boost the growth of the global natural language processing market in the coming years.

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