Speech and Voice Recognition Market by Deployment Mode (On-Cloud, On-Premises/Embedded), Technology (Speech Recognition, Voice Recognition), Vertical and Geography (Americas, Europe, APAC, Rest of the World) - Global Forecast to 2027
[279 Pages Report] The speech and voice recognition market size is valued at USD 9.4 billion in 2022 and is anticipated to be USD 28.1 billion by 2027; growing at a CAGR of 24.4% from 2022 to 2027. Factors such as increasing demand in healthcare for improving efficiency and the growing use of smart appliances are driving the growth of the market during the forecast period.
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COVID-19 Impact
The speech and voice recognition market has been witnessing significant growth over the years owing to the increasing demand for speech and voice-based biometric systems for Multifactor authentication, the growing impact of AI on the accuracy of speech and voice recognition, and the rapid proliferation of smart speakers. The COVID-19 pandemic affected the market positively and negatively. The demand for smart appliances and devices has increased, with most of the population working from home. This has also created an opportunity for speech and voice recognition providers. However, many people also focused on maintaining the basic lifestyle during the pandemic, avoiding purchasing luxurious or non-essential products for a short period.
Speech And Voice Recognition Market Dynamics
Driver: Escalated use of speech and voice recognition software by healthcare professionals
Many healthcare professionals spend a significant amount of time typing notes and reports and maintaining each patient's medical records as documenting every minute detail is of utmost importance in healthcare. However, these tasks take time from more productive chores such as treating and interacting personally with patients. Hence, doctors and physicians prefer using natural language processing (NLP) algorithm-based voice recognition software solutions. Speech and voice recognition technologies are mostly used in the healthcare sector to report health checkups, data entry, and when the doctor or the attendant/nurse is unavailable. Such software solutions enable healthcare professionals to enter notes into the electric health record (EHR) system or their computers without taking time out from patient care and remain productive throughout the day. This eliminates the need for healthcare providers to stay late at work to complete paperwork, allowing them to visit more patients during the day. Easy to use and hands-free features of an automated speech recognition system in medical applications enable doctors to get their work done efficiently, driving the speech and voice recognition market growth. Thus, increased productivity leads to increased cash flow.
Restraint: Limitation of software to understand contextual relation of words in different languages
Words with similar sounds but different meanings are called homophones, for example, "right/write" or "bye/by/buy." AI may struggle to identify homophones in a sentence without a comprehensive language model and training on these terms with reference to appropriate contexts. Many terms in English and Roman languages have several meanings. For instance, the “cell” can be a part of an organism, a prison room, or an area of radio coverage (cell phone). Also, heteronyms with diverse meanings are common in most languages. For example, in English, "close" means "to shut" or "near," and "converse" means "to talk" or "the opposite." Therefore, it might not be easy to know when to use the correct homonyms while translating the content. To solve this challenge, the translator must be well-versed with the spoken language and the language in which the text will be translated. This may necessitate the in-depth understanding of both languages by the translator.
Opportunity:Increasing popularity of online shopping
Customer buying behavior is shifting in both developed and developing countries. There is a trend of buying things online. Customers may shop products, enquire about prices and features from the comfort of their own homes, and even receive personalized recommendations based on their previous purchases. This experience can be made even more frictionless and participatory with the use of voice assistants. According to the Conversational Commerce Survey by Capgemini in 2017, 41% of consumers prefer a voice assistant to a website or app while shopping online since it allows them to automate their usual shopping operations. Searching for products and services, creating a shopping list, adding items to a shopping cart, making a purchase, checking the status of orders, providing feedback on products and services, using the customer support service, and making recommendations for the product or service to other potential customers are just a few of the customer touchpoints where voice assistants can be useful. Customers' faster adoption and usage of voice assistants, along with a surge in online commerce, present an opportunity for voice assistant application solutions and service providers.
Challenge: Increased errors due to background noise
A quiet environment is important for the smooth working of speech and voice recognition technology. Too much background noise can affect the results of speech and voice recognition. One of the major challenges of using speech and voice recognition technologies effectively in outdoor environments or large public spaces and offices.
Consumers of speech recognition technology largely measure its performance based on accuracy and speed. Accuracy of speech recognition is measured using the word error rate (WER). Despite recent advancements, the WER of speech and voice recognition technologies cannot match the WER of humans. In a survey of smartphone owners on their expectations for improvements in voice assistants,' accuracy' received 40% of the votes. Speech and voice recognition aims to convert a speech signal accurately and efficiently into a text message. Companies are developing complex algorithms and focusing on deep learning to make speech and voice recognition systems more robust. However, the systems are not 100% accurate and efficient, and further developments and research activities are in progress to make them effective even in noisy environments.
In the coming years, companies that focus more on eliminating this problem through deeper research have more chances of providing better products and applications that can better adapt to users' speaking habits and reduce the rate of errors by differentiating background noise from that of the user.
APAC held the largest market for the speech and voice recognition market in 2027 owing to the technological advancements and the rising demand for speech and voice recognition systems in the medical.
During the forecast period, APAC held the largest share of market in 2027 and is expected to continue its upward growth trend. From 2022 to 2027, the region is expected to have the highest CAGR. The speech and voice recognition market in Asia Pacific is growing owing to technological advancements, improved awareness regarding the benefits of these technologies among the masses, and the low cost of speech and voice recognition devices. China, Japan, and India are the key countries in the Asia Pacific region for market. Baidu (China) and iFlytek (China) are the top two companies in the region operating in the speech and recognition market. The surge in the adoption of voice assistant devices in China is the major reason for the market growth. The constant developments in healthcare and other applications will accelerate the demand for voice recognition technology-based products in the region. The market in India is expected to witness the highest growth during the forecast period.
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Key Market Players
The speech and voice recognition market is dominated by a few globally established players such as Apple (US), Microsoft (US), IBM (US), Alphabet (US), Amazon (US), Baidu (China), iFlytek (China) and SESTEK (Turkey), speak2web (US), and Verint (US).
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|
Report Metric |
Scope |
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Market size available for years |
2018–2027 |
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Base year considered |
2021 |
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Forecast period |
2022–2027 |
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Forecast units |
Value (USD Million) and Volume (Thousand Units) |
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Segments covered |
By Technology, By Deployment mode, By Vertical, and By Region. |
|
Geographies covered |
Americas, Europe, Asia Pacific, and Rest of World |
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Companies covered |
The key players in the speech and voice recognition market are Apple (US), Microsoft (US), IBM (US), Alphabet (US), Amazon (US),Baidu (China), iFLYTEK (China) and SESTEK (Turkey), speak2web (US), and Verint (US), Speechmatics (UK), Deepgram (US), Voiceitt (Israel), Voicegain( US), Sensory (US), AssemblyAI (US), Verbit (US), Otter.aI (US), Rev (US), Raytheon BBN Technologies (US), M2SYS (US), M*Modal (US), ValidSoft (UK), LumenVox (US), Acapela Group (Belgium), VocalZoom (Israel), Uniphore Software (India), iSpeech (US), GoVivace (US), Advanced Voice recognition systems (Arizona), Dolbey (US), ReadSpeaker (Netherlands), Pareteum Corporation (US), SoundHound Inc (US). |
The study categorizes the speech and voice recognition market based on Technology, Deployment mode, Vertical, and Region.
By Technology:
- Speech Recognition
- Automatic Speech Recognition
- Text-To-Speech
- Voice Recognition
- Speaker Identification
- Speaker Verification
By Deployment mode:
- On Cloud
- On-Premises/Embedded
By Vertical:
- Automotive
- Enterprise
- Consumer
- Banking, Finance Service & Insurance (BFSI)
- Government
- Retail
- Healthcare
- Military
- Legal
- Education
- Others
By Region:
- Americas
- Europe
- APAC
- RoW
Recent Developments
- In April 2021, Verint launched Verint Virtual Assistant (IVA), a low-code conversational AI offering, which can rapidly turn the existing conversation data into automated self-service experiences. It allows business professionals to quickly deploy a production-ready chatbot to deflect calls and support customers. Verint IVA enables businesses to expand capabilities across the enterprise with boundless intelligence for both voice and digital.
- In September 2020, Microsoft and Nuance Communications introduced Nuance Dragon Ambient eXperience (DAX), an ambient clinical intelligence (ACI) solution, to integrate it into Microsoft Teams to broadly scale virtual consults aimed at increasing physician wellness and providing better patient health outcomes.
- In December 2019, Amazon Web Services introduced Amazon Transcribe Medical, an automated speech recognition service that will help developers add medical dictation and documentation to their apps.
- In March 2018, IBM launched Watson Assistant, a smart enterprise voice recognition and the assistant system powered by AI, cloud, and IoT.
Frequently Asked Questions (FAQ):
What is the current size of the global speech and voice recognition market?
The speech and voice recognition market size is valued at USD 9.4 Billion in 2022 and is anticipated to be USD 28.1 Billion by 2027; growing at a CAGR of 24.4 % from 2022 to 2027
Which is the potential market for speech and voice recognition solution in terms of region?
The APAC region is expected to dominate the speech and voice recognition market due to the technological developments and growing awareness about the features of speech and voice recognition systems.
Which is the key vertical that dominates speech and voice recognition market?
The consumer segment is significantly growing in the speech and voice recognition market.
What are the key strategies adopted by key companies in the speech and voice recognition market?
The key companies have been focusing on product launches and development to significantly grow in the speech and voice recognition market.
Which are the major companies in the speech and voice recognition market?
Apple (US), Microsoft (US), IBM (US), Alphabet (US), Amazon (US),Baidu (China), iFlytek (China) and SESTEK (Turkey), speak2web (US), and Verint (US) are the players dominating the global speech and voice recognition market. .
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TABLE OF CONTENTS
1. INTRODUCTION
1.1. Objective of the Study
1.2. Market Definition
1.3. Study Scope
1.3.1. Markets Covered
1.3.2. Geographic Scope
1.3.3. Years Considered for the Study
1.4. Currency
1.5. Stakeholders
1.6. Summary of Changes
2. RESEARCH METHODOLOGY
2.1. Research Data
2.1.1. Secondary Data
2.1.2. Primary Data
2.2. Market Size Estimation
2.2.1. Bottom-Up Approach
2.2.2. Top-Down Approach
2.3. Market Breakdown and Data Triangulation
2.4. Research Assumptions
2.5. Risk Assessment
2.6. Limitations
3. EXECUTIVE SUMMARY
3.1. Speech and Voice Recognition Market: Post COVID-19
3.2. Realistic Scenario
3.3. Pessimistic Scenario
3.4. Optimistic Scenario
4. PREMIUM INSIGHTS
5. MARKET OVERVIEW
5.1. Introduction
5.2. Market Dynamics
5.2.1. Drivers
5.2.2. Restraints
5.2.3. Opportunities
5.2.4. Challenges
5.3. Value Chain Analysis
5.4. Porter’s Five Forces Analysis
5.5. Average Selling Pricing Analysis
5.6. Trade Analysis
5.7. Ecosystem Analysis
5.8. Case Study Analysis
5.9. Patent Analysis
5.10. Technology Analysis
5.11. Codes and Standards
5.12. Tariff Analysis
5.13. Regulatory Bodies, Government Agencies & Other Organizations
5.14. Revenue Shift
5.15. Key Conferences and Events in 2022-2023
5.16. Key Stakeholder and buying and/or buying criteria
5.16.1. Key Stakeholders in buying process
5.16.2. Buying Criteria
6. SPEECH AND VOICE RECOGNITION MARKET, BY DELIVERY METHOD
6.1. Introduction
6.2. Artificial Intelligence – Based
6.3. Non- Artificial Intelligence – Based
7. MARKET, BY TECHNOLOGY
7.1. Introduction
7.2. Voice Recognition
7.2.1. Speaker Identification
7.2.2. Speaker Verification
7.3. Speech Recognition
7.3.1. Multilingual Speech Recognition to Increase Scope of Applications
7.3.2. Automatic Speech Recognition
7.3.3. Text-to-Speech
8. SPEECH AND VOICE RECOGNITION MARKET, BY DEPLOYMENT MODE
8.1. Introduction
8.2. On Cloud
8.3. On-Premises/Embedded
9. MARKET, BY VERTICAL
9.1. Introduction
9.2. Automotive
9.3. Enterprises
9.4. Consumer
9.5. Banking, Financial Services and Insurance (BFSI)
9.6. Government
9.7. Retail
9.8. Healthcare
9.9. Military
9.10. Legal
9.11. Education
9.12. Others
10. SPEECH AND VOICE RECOGNITION MARKET, BY GEOGRAPHY
10.1. Introduction
10.2. Americas
10.2.1. US
10.2.2. Canada
10.2.3. Rest of Americas
10.3. Europe
10.3.1. UK
10.3.2. Germany
10.3.3. France
10.3.4. Rest of Europe
10.4. APAC
10.4.1. Japan
10.4.2. China
10.4.3. India
10.4.4. Rest of APAC
10.5. Rest of the World (RoW)
10.5.1. Middle East
10.5.2. Africa
11. COMPETITIVE LANDSCAPE
11.1. Introduction
11.2. Top 5 Company Revenue Analysis
11.3. Strategies adopted by key players
11.4. Market Share Analysis
11.5. Company Evaluation Matrix
11.5.1. Star
11.5.2. Pervasive
11.5.3. Emerging Leaders
11.6. Strength of Product Portfolio
11.7. Business Strategy Excellence
11.8. Small and Medium Enterprises (SME) Evaluation Quadrant
11.8.1. Progressive Companies
11.8.2. Responsive Companies
11.8.3. Dynamic Companies
11.8.4. Starting Blocks
11.9. Competitive Situation And Trends
11.10. Competitive Benchmarking
12. COMPANY PROFILE
12.1. Introduction
12.2. Key Companies
12.2.1. Hexagon
12.2.2. Faro Technologies
12.2.3. Nikon Metrology
12.2.4. Carl Zeiss
12.2.5. Jenoptik
12.2.6. Creaform
12.2.7. KLA-Tencor
12.2.8. Renishaw
12.2.9. GOM
12.2.10. Mitutoyo Corporation
12.3. Other Players
12.3.1. Precision Products
12.3.2. Carmar Accuracy
12.3.3. Baker Hughes
12.3.4. CyberOptics
12.3.5. Cairnhill Metrology
12.3.6. Att Metrology Services
12.3.7. SGS Group
12.3.8. TriMet Group
12.3.9. Automated Precision
12.3.10. Applied Materials
12.3.11. Perceptron
12.3.12. JLM Advanced Technical Services
12.3.13. Intertek
12.3.14. Bruker
12.3.15. Metrologic Group
12.3.16. Speechmatics,
12.3.17. DeepGram,
12.3.18. Assembly.ai
12.3.19. Verbit
12.3.20. Voiceitt
12.3.21. Otter.ai,
12.3.22. Voicegain
12.3.23. Sensory
12.3.24. rev.com
13. Appendix
13.1. Insights of Industry Experts
13.2. Discussion Guide
13.3. Knowledge Store: MarketsandMarkets’ Subscription Portal
13.4. Available Customizations
13.5. Related Reports
13.6. Author Details
Note: This ToC is tentative and minor changes are possible as the study progresses.
The study involved four major activities in estimating the size of the speech and voice recognition market. Exhaustive secondary research has been done to collect information on the market, peer market, and parent market. Validation of these findings, assumptions, and sizing with industry experts across the value chain through primary research has been the next step. Both top-down and bottom-up approaches have been employed to estimate the global market size. After that, market breakdown and data triangulation have been used to estimate the market sizes of segments and subsegments.
Secondary Research
The secondary sources referred to for this research study includes corporate filings (such as annual reports, press releases, investor presentations, and financial statements); trade, business, and professional associations (such as Consumer Technology Association (CTA), Integrated Systems Europe, the Organisation Internationale des Constructeurs d'Automobiles (OICA), the Society for Information Display (SID), and Touch Taiwan); white papers, certified publications, and articles by recognized authors; gold and silver standard websites; directories; and databases.
Secondary research has been conducted to obtain key information about the supply chain of the speech and voice recognition industry, the monetary chain of the market, the total pool of key players, and market segmentation according to the industry trends to the bottommost level, regional markets, and key developments from both market- and technology oriented perspectives. The secondary data has been collected and analyzed to arrive at the overall market size, which has further been validated by primary research.
Primary Research
Extensive primary research has been conducted after acquiring an understanding of the speech and voice recognition market scenario through secondary research. Several primary interviews have been conducted with market experts from both the demand- (consumers, industries) and supply-side (speech and voice recognition device manufacturers) players across four major regions, namely, Americas, Europe, Asia Pacific, and the Rest of the World (the Middle East & Africa). Approximately 75% and 25% of primary interviews have been conducted from the supply and demand side, respectively. Primary data has been collected through questionnaires, emails, and telephonic interviews. In the canvassing of primaries, various departments within organizations, such as sales, operations, and administration, were covered to provide a holistic viewpoint in our report.
After interacting with industry experts, brief sessions were conducted with highly experienced independent consultants to reinforce the findings from our primaries. This, along with the in-house subject matter experts’ opinions, has led us to the findings as described in the remainder of this report.
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
Both top-down and bottom-up approaches have been used to estimate and validate the total size of the speech and voice recognition market. These methods have also been extensively used to estimate the sizes of various market subsegments. The research methodology used to estimate the market sizes includes the following:
- Identifying various applications that use or are expected to use the speech and voice recognition market.
- Analyzing historical and current data pertaining to the size of the speech and voice recognition market, in terms of volume, for each application using their production statistics
- Analyzing the average selling prices of speech and voice recognition based on different technologies
- Studying various paid and unpaid sources, such as annual reports, press releases, white papers, and databases
- Identifying leading manufacturers of speech and voice recognition sensors, studying their portfolios, and understanding features of their products and their underlying technologies, as well as the types of speech and voice recognition offered
- Tracking ongoing and identifying upcoming developments in the market through investments, research and development activities, product launches, expansions, and partnerships, and forecasting the market size based on these developments and other critical parameters
- Carrying out multiple discussions with key opinion leaders to understand the technologies used in speech and voice recognition, raw materials used to develop them, and products wherein they are deployed, and analyze the break-up of the scope of work carried out by key manufacturers of speech and voice recognition solutions providers
- Verifying and crosschecking estimates at every level through discussions with key opinion leaders, such as CXOs, directors, and operations managers, and finally with domain experts at MarketsandMarkets
Market Size Estimation Methodology-Bottom-up approach
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Data Triangulation
After arriving at the overall market size using the market size estimation processes explained above—the market has been split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakdown procedures have been employed, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides.
The main objectives of this study are as follows:
- To define, describe, segment, and forecast the speech and voice recognition market, in terms of value, based on technology, deployment mode, vertical, and region.
- To forecast the speech and voice recognition market, in terms of volume, based on application
- To forecast the size of the market and its segments with respect to four main regions, namely, Americas, Europe, Asia Pacific (APAC), and the Rest of the World (RoW), along with their key countries
- To strategically analyze micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
- To provide detailed information regarding the key factors influencing market growth, such as drivers, restraints, opportunities, and challenges
- To provide a detailed analysis of the speech and voice recognition supply chain
- To analyze the opportunities in the market for stakeholders and provide a detailed competitive landscape of the market leaders
- To strategically profile the key players and comprehensively analyze their market ranking and core competencies2
- To analyze key growth strategies such as expansions, contracts, joint ventures, acquisitions, product launches and developments, and research and development activities undertaken by players operating in the speech and voice recognition market.
Available Customizations:
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- Further breakdown of the market in different regions to the country-level
- Detailed analysis and profiling of additional market players (up to 5)
- Triangulate with your Own Data
- Get Data as per your Format and Definition
- Gain a Deeper Dive on a Specific Application, Geography, Customer or Competitor
- Any level of Personalization
- What are the Known and Unknown Adjacencies Impacting the Speech and Voice Recognition Market
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Growth opportunities and latent adjacency in Speech and Voice Recognition Market