The Global Speech-to-text API Market size is expected to reach $5.8 billion by 2027, rising at a market growth of 19.0% CAGR during the forecast period.
The speech-to-text application programming interface (API) is a programming interface that enables the utilization of speech synthesis and recognition in a variety of devices and applications. Speech-to-text API is a multidisciplinary subject of computational linguistics that explores methods that allow computers to translate and recognize audible language into text. This is also called as Automatic Speech Recognition (ASR) or Speech-to-Text.
It encompasses electrical engineering, computer science, and linguistics research and knowledge. Deep learning and big data advancements have aided the field in recent years. The progress is evidenced not only by the rapid increase in the number of academic papers published in the subject but also by the widespread industry use of a range of deep learning approaches in the design and implementation of voice recognition systems around the world.
Any video or audio-based information can be captioned and subtitled using the speech-to-text API technology, allowing struggling listeners or learners with visual impairments to understand and complete their work without assistance. Speech-to-text APIs, for example, can help students with hearing loss communicate with their teachers and peers. However, the key obstacles in the speech-to-text API market are multilingual support for captioning and subtitling, as well as establishing unique vocabulary across multiple verticals.
Many organizations witnessed increased consumer pressure during the pandemic, while their number of available workers was reduced. Many contact centers were unable to meet demand or were forced to close due to lockdown restrictions, resulting in high wait times for customer service requests and a negative impact on the customer experience. Speech-to-text API is moving to the forefront of technology enablers as companies adopt a more strategic strategy that offers resilience into operations through flexibility and scalability while also working to increase operational efficiencies.
Medical speech recognition capabilities are sought by data analytics application developers to assist them swiftly and accurately transcribing video and audio incorporating COVID-19 terminology into text for downstream analytics. Amazon Transcribe Medical, for example, is a fully managed speech recognition (ASR) service that makes it simple to add medical speech-to-text capabilities to any application.
With the widespread acceptance of technology and the vast development of internet-based material, the demand for smart devices such as smart speakers and mobile phones has increased over the last decade, resulting in a greater need to make online video content available to everyone. Several new advanced gadgets with voice-controlled functions, such as content transcription and conference call analysis, are being introduced, allowing consumers to access educational, entertainment, and other information via their smart devices. As a result of the rising requirement to understand client preferences, speech-to-text apps have grown in popularity.
Several organizations collect client data about media material and translate it into texts to assist content providers in determining what types of content are acceptable and becoming more popular. Moreover, the demand for smart homes and smart appliances is rising as a result of a number of factors, including rising internet penetration, technological improvements, and increased awareness of automation.
Any video or audio-based content can be translated by a computer into text using the speech-to-text API technology, which allows struggling listeners or hard-of-hearing students read appropriately and complete their work without the assistance of others. Speech-to-text software, for example, can help a deaf-mute student interact with his or her professors and classmates. As a result, this system functions as assistive technology, allowing impaired persons to take advantage of ICT. For impaired students, the Individuals with Disabilities Education Act (IDEA) provides interactive software. In the classroom, these students are unable to hear well.
To address this, professors at Northern Illinois University, created an interactive software lesson that uses speech-to-text technology to assist these students in learning the Nemeth code (a Braille code for mathematics).
Transcribing audio from numerous channels is a significant barrier for this technology since defining many things becomes challenging, resulting in erroneous transcriptions or captions. In addition, background noise, low-quality microphones, reverb and echo, and accent changes all have the potential to degrade transcription accuracy.
Voice-to-text APIs should be appropriately trained for multi-channel speech recognition using a number of data sets; however, gathering a variety of data sets for establishing an approach and solution that accurately converts speech-to-text for many channels can be problematic for businesses. Moreover, privacy concerns about voice-enabled gadgets is expected to discourage many entities to embrace these solutions.
Based on Component, the market is segmented into Solution and Services. In 2020, the Solutions segment acquired the highest revenue share of the speech-to-text market. APIs and Software Development Kits (SDKs) in the software market enable existing software or applications to convert video-based material to text format. The suppliers also provide related solutions to help streamline processes and create seamless results. To deal with the quickly rising video-based material, leading companies in numerous industries are using speech-to-text API. This is assisting businesses in discovering new methods to tap into the vast amounts of data available in order to produce new products, services, and processes, so gaining a competitive advantage.
Based on Vertical, the market is segmented into BFSI, IT & Telecom, Healthcare, Retail & eCommerce, Government & Defense, Media & Entertainment, Travel & Hospitality, and Others. The IT & Telecom segment obtained a significant revenue share of the Speech-to-text market in 2020. Through speech recognition, analytics, and reporting, the IT and telecom industries appear to be adopting voice technology to automate and enhance customer experience. Moreover, a growing number of IT and telecom companies are utilizing these solutions to streamlines their communication and other business operations.
Based on Organization Size, the market is segmented into Large Enterprises and Small & Medium-sized Enterprises (SMEs). The SMEs segment obtained a significant revenue share of the Speech-to-text market in 2020. The growth of the segment is due to growing competition from emerging SMEs in large corporations. In addition, many SMEs are slowly moving towards the deployment of new and advanced solutions to provide enhanced customer experience.
Based on Deployment Type, the market is segmented into Cloud and On-premise. In 2020, the Cloud segment acquired the largest revenue share of the Speech-to-text market. The advantages of cloud technology, such as ease of deployment and low capital requirements, make it easier to embrace the cloud deployment paradigm. The COVID-19 pandemic is likely to encourage enterprises to switch to cloud-based speech-to-text API solutions that can be administered remotely, as lockdowns and social distancing practices encourage companies to move to cloud-based speech-to-text API solutions. The cloud segment of the speech-to-text API market is expected to grow further with the growing demand for scalable, easy-to-use, and cost-effective speech-to-text API solutions.
Based on Application, the market is segmented into Fraud Detection & Prevention, Contact Center & Customer Management, Risk & Compliance Management, Content Transcription, Subtitle Generation, and Others. In 2020, the Fraud Detection & Prevention segment acquired the largest revenue share of the Speech-to-text market. This is due to the increased need for speech-to-text APIs in the media and entertainment business to transcribe audio and video content into searchable and shareable text.
Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. In 2020, North America emerged as the leading region in the overall Speech-to-text market. In addition, the regional market is expected to showcase a similar kind of trend even during the forecasting period. This is because of its substantial technology spending and the simple availability of solutions with a significant presence of suppliers. In addition, the regional market is expected to grow further due to the growing requirement to extract relevant insights from voice data.
The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Google LLC and Microsoft Corporation are the forerunners in the Speech-to-text API Market. Companies such as IBM Corporation, Amazon Web Services, Inc., Baidu, Inc. are some of the key innovators in the Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include LivePerson, Inc. (VoiceBase, Inc.), VoiceCloud LLC, Speechmatics Ltd., IBM Corporation, Microsoft Corporation, Google LLC, Baidu, Inc., Twilio, Inc., Amazon Web Services, Inc., and Verint Systems, Inc.
By Component
By Vertical
By Organization Size
By Deployment Type
By Application
The speech-to-text application programming interface (API) is a programming interface that enables the utilization of speech synthesis and recognition in a variety of devices and applications. Speech-to-text API is a multidisciplinary subject of computational linguistics that explores methods that allow computers to translate and recognize audible language into text. This is also called as Automatic Speech Recognition (ASR) or Speech-to-Text.
It encompasses electrical engineering, computer science, and linguistics research and knowledge. Deep learning and big data advancements have aided the field in recent years. The progress is evidenced not only by the rapid increase in the number of academic papers published in the subject but also by the widespread industry use of a range of deep learning approaches in the design and implementation of voice recognition systems around the world.
Any video or audio-based information can be captioned and subtitled using the speech-to-text API technology, allowing struggling listeners or learners with visual impairments to understand and complete their work without assistance. Speech-to-text APIs, for example, can help students with hearing loss communicate with their teachers and peers. However, the key obstacles in the speech-to-text API market are multilingual support for captioning and subtitling, as well as establishing unique vocabulary across multiple verticals.
COVID-19 Impact Analysis
Many organizations witnessed increased consumer pressure during the pandemic, while their number of available workers was reduced. Many contact centers were unable to meet demand or were forced to close due to lockdown restrictions, resulting in high wait times for customer service requests and a negative impact on the customer experience. Speech-to-text API is moving to the forefront of technology enablers as companies adopt a more strategic strategy that offers resilience into operations through flexibility and scalability while also working to increase operational efficiencies.
Medical speech recognition capabilities are sought by data analytics application developers to assist them swiftly and accurately transcribing video and audio incorporating COVID-19 terminology into text for downstream analytics. Amazon Transcribe Medical, for example, is a fully managed speech recognition (ASR) service that makes it simple to add medical speech-to-text capabilities to any application.
Market Growth Factors:
The massive penetration of smartphones is creating the requirement for voice-based devices
With the widespread acceptance of technology and the vast development of internet-based material, the demand for smart devices such as smart speakers and mobile phones has increased over the last decade, resulting in a greater need to make online video content available to everyone. Several new advanced gadgets with voice-controlled functions, such as content transcription and conference call analysis, are being introduced, allowing consumers to access educational, entertainment, and other information via their smart devices. As a result of the rising requirement to understand client preferences, speech-to-text apps have grown in popularity.
Several organizations collect client data about media material and translate it into texts to assist content providers in determining what types of content are acceptable and becoming more popular. Moreover, the demand for smart homes and smart appliances is rising as a result of a number of factors, including rising internet penetration, technological improvements, and increased awareness of automation.
The growing number of advanced speech-to-text solutions for differently-abled students
Any video or audio-based content can be translated by a computer into text using the speech-to-text API technology, which allows struggling listeners or hard-of-hearing students read appropriately and complete their work without the assistance of others. Speech-to-text software, for example, can help a deaf-mute student interact with his or her professors and classmates. As a result, this system functions as assistive technology, allowing impaired persons to take advantage of ICT. For impaired students, the Individuals with Disabilities Education Act (IDEA) provides interactive software. In the classroom, these students are unable to hear well.
To address this, professors at Northern Illinois University, created an interactive software lesson that uses speech-to-text technology to assist these students in learning the Nemeth code (a Braille code for mathematics).
Marketing Restraining Factor:
Transcribing audio from many channels could stymie the market for speech-to-text APIs.
Transcribing audio from numerous channels is a significant barrier for this technology since defining many things becomes challenging, resulting in erroneous transcriptions or captions. In addition, background noise, low-quality microphones, reverb and echo, and accent changes all have the potential to degrade transcription accuracy.
Voice-to-text APIs should be appropriately trained for multi-channel speech recognition using a number of data sets; however, gathering a variety of data sets for establishing an approach and solution that accurately converts speech-to-text for many channels can be problematic for businesses. Moreover, privacy concerns about voice-enabled gadgets is expected to discourage many entities to embrace these solutions.
Component Outlook
Based on Component, the market is segmented into Solution and Services. In 2020, the Solutions segment acquired the highest revenue share of the speech-to-text market. APIs and Software Development Kits (SDKs) in the software market enable existing software or applications to convert video-based material to text format. The suppliers also provide related solutions to help streamline processes and create seamless results. To deal with the quickly rising video-based material, leading companies in numerous industries are using speech-to-text API. This is assisting businesses in discovering new methods to tap into the vast amounts of data available in order to produce new products, services, and processes, so gaining a competitive advantage.
Vertical Outlook
Based on Vertical, the market is segmented into BFSI, IT & Telecom, Healthcare, Retail & eCommerce, Government & Defense, Media & Entertainment, Travel & Hospitality, and Others. The IT & Telecom segment obtained a significant revenue share of the Speech-to-text market in 2020. Through speech recognition, analytics, and reporting, the IT and telecom industries appear to be adopting voice technology to automate and enhance customer experience. Moreover, a growing number of IT and telecom companies are utilizing these solutions to streamlines their communication and other business operations.
Organization Size Outlook
Based on Organization Size, the market is segmented into Large Enterprises and Small & Medium-sized Enterprises (SMEs). The SMEs segment obtained a significant revenue share of the Speech-to-text market in 2020. The growth of the segment is due to growing competition from emerging SMEs in large corporations. In addition, many SMEs are slowly moving towards the deployment of new and advanced solutions to provide enhanced customer experience.
Deployment Type Outlook
Based on Deployment Type, the market is segmented into Cloud and On-premise. In 2020, the Cloud segment acquired the largest revenue share of the Speech-to-text market. The advantages of cloud technology, such as ease of deployment and low capital requirements, make it easier to embrace the cloud deployment paradigm. The COVID-19 pandemic is likely to encourage enterprises to switch to cloud-based speech-to-text API solutions that can be administered remotely, as lockdowns and social distancing practices encourage companies to move to cloud-based speech-to-text API solutions. The cloud segment of the speech-to-text API market is expected to grow further with the growing demand for scalable, easy-to-use, and cost-effective speech-to-text API solutions.
Application Outlook
Based on Application, the market is segmented into Fraud Detection & Prevention, Contact Center & Customer Management, Risk & Compliance Management, Content Transcription, Subtitle Generation, and Others. In 2020, the Fraud Detection & Prevention segment acquired the largest revenue share of the Speech-to-text market. This is due to the increased need for speech-to-text APIs in the media and entertainment business to transcribe audio and video content into searchable and shareable text.
Regional Outlook
Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. In 2020, North America emerged as the leading region in the overall Speech-to-text market. In addition, the regional market is expected to showcase a similar kind of trend even during the forecasting period. This is because of its substantial technology spending and the simple availability of solutions with a significant presence of suppliers. In addition, the regional market is expected to grow further due to the growing requirement to extract relevant insights from voice data.
Cardinal Matrix - Speech-to-text API Market Competition Analysis
The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Google LLC and Microsoft Corporation are the forerunners in the Speech-to-text API Market. Companies such as IBM Corporation, Amazon Web Services, Inc., Baidu, Inc. are some of the key innovators in the Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include LivePerson, Inc. (VoiceBase, Inc.), VoiceCloud LLC, Speechmatics Ltd., IBM Corporation, Microsoft Corporation, Google LLC, Baidu, Inc., Twilio, Inc., Amazon Web Services, Inc., and Verint Systems, Inc.
Recent Strategy Deployed in Speech-to-text API Market
Partnerships, Collaborations and Agreements:
- Sep-2021: Microsoft joined hands with CallMiner, a leading provider of conversation analytics. Following the collaboration, the world-class conversation analytics platform of CallMiner is expected to be integrated with the speech recognition solution of Microsoft. Through this integration, companies is expected to achieve higher value in their present tools and get a thorough understanding of customer conversations. By getting valuable insights, companies can help contact centers to enhance customer experiences and agent performance, and make informed business decisions across each department.
- Jun-2021: Microsoft collaborated with ICICI Lombard, a general insurance company in India. Under this collaboration, Microsoft is expected to help ICICI Lombard to improve and automate the quality control processes. Moreover, ICICI Lombard is expected to leverage the Azure Speech Services and Natural Language Processing (NLP) of Microsoft to monitor its daily service calls made by customer service representatives. With the implementation of Azure's artificial tools, ICICI Lombard can enhance the accuracy of its quality audits.
- Jan-2021: Microsoft formed a collaboration with Yellow Messenger, the world’s leading conversational AI platform. Following the collaboration, Yellow Messenger is expected to transform its voice automation solution with the help of Azure AI Speech Services and Natural Language Processing (NLP) tools. Through this collaboration, Microsoft is expected to help Yellow Messenger to develop customized voice models that enable superior accuracy and higher intent understanding.
- Jan-2021: Amazon Web Services teamed up with Talkdesk, the cloud contact center for innovative enterprises. Following the collaboration, the integration of unique, cloud-native capabilities from Talkdesk CX Cloud with robust AI and machine learning services from AWA, provides Talkdesk customers with the flexibility, agility, and insight to better manage contact center operations and enhanced customer experience. Under this collaboration, Talkdesk Agent Assist and Talkdesk Speech Analytics is expected to harness the potential of Amazon Transcribe to increase the number of languages and accents in the products being available.
- Aug-2020: Speechmatics partnered with Prosodica, a provider of innovative voice and audio analysis technology and a subsidiary of Vail Systems. Following the partnership, the two companies is expected to offer superior call experiences to improve customer care and enhance customer experiences.
- Jun-2020: Speechmatics came into a partnership with Daisee, a leading provider of speech analytics software. Through this partnership, the two companies is expected to allow enterprises to comprehend and focus on the customer calls with the help of Lisa, a speech and sentiment analysis software.
Product Launches and Product Expansions:
- Nov-2021: Baidu unveiled PLATO-XL, an AI model for dialog generation. The new model is trained on more than a billion samples from social media conversations in English as well as Chinese. Moreover, PLATO-XL promises advanced performance on various conversational benchmarks, outperforming presently available commercial chatbots.
- Sep-2021: IBM rolled out the latest AI and automation capabilities in IBM Watson Assistant. Through these new capabilities, IBM is expected to make it easier for enterprises to develop improved customer service experiences across any channel-phone, SMS, web, and any messaging platform.
- Aug-2021: AWS introduced Amazon Transcribe Call Analytics, a new feature that allows the easy extraction of beneficial insights from customer conversations with a single API call. The new solution includes natural language processing (NLP) capabilities particularly trained on customer calls and enhanced to offer extremely precise call transcripts and beneficial insights. By a simple API call, developers can effortlessly include call analytics in any application and obtain customer insights from conversations without the need to create AI pipelines and train custom ML models.
- Aug-2021: IBM introduced new features in its IBM Watson Speech to Text technology. The new features can transcribe Indian English and Hindi language audios. Moreover, these latest services were developed with the help of advanced models that provide extremely high throughput and transcription accuracy.
- Apr-2021: Verint unveiled Verint Intelligent Virtual Assistant Professional (IVA Pro) Package, a low-code conversational artificial intelligence (AI) offering that can easily transform current conversation data into automated self-service experiences. The package is a part of the prominent Verint Intelligent Virtual Assistant (IVA) offering and enables business professionals to rapidly implement a production-ready chatbot to divert calls and support customers.
- Nov-2020: Speechmatics rolled out a first-of-its-kind Global Spanish language pack for automatic speech-to-text transcription at scale. Through this launch, the company aimed to offer an enhanced user experience with no extra software or complicated processes required. The new solution is rapid, precise, robust, more flexible, convenient, and inclusive.
- Aug-2020: AWS unveiled AWS Contact Center Intelligence (CCI) solutions, an integration of services that allow customers to effortlessly combine AI into contact centers. Moreover, Machine learning capabilities like as transcription, text-to-speech, translation, corporate search, chatbots, business intelligence, and language comprehension may all be integrated into current contact center systems using AWS CCI solutions. In addition, customers can deploy contact center intelligence ML solutions to help self-service, post-call analytics, and live-call analytics & agent assist.
- Apr-2020: Microsoft rolled out the latest neural text-to-speech (TTS) capabilities in Azure Cognitive Services. The new capabilities include three latest styles viz. newscast, customer service, and a digital assistant that allow natural-sounding speech and match the pattern and intonations of human voices.
Scope of the Study
Market Segments Covered in the Report:
By Component
- Solution
- Services
By Vertical
- BFSI
- IT & Telecom
- Healthcare
- Retail & eCommerce
- Government & Defense
- Media & Entertainment
- Travel & Hospitality
- Others
By Organization Size
- Large Enterprises
- Small & Medium-sized Enterprises (SMEs)
By Deployment Type
- Cloud
- On-premise
By Application
- Fraud Detection & Prevention
- Contact Center & Customer Management
- Risk & Compliance Management
- Content Transcription
- Subtitle Generation
- Others
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Key Market Players
List of Companies Profiled in the Report:
- LivePerson, Inc. (VoiceBase, Inc.)
- VoiceCloud LLC
- Speechmatics Ltd.
- IBM Corporation
- Microsoft Corporation
- Google LLC
- Baidu, Inc.
- Twilio, Inc.
- Amazon Web Services, Inc.
- Verint Systems, Inc.
Unique Offerings from the Publisher
- Exhaustive coverage
- The highest number of market tables and figures
- Subscription-based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
Chapter 3. Competition Analysis - Global
Chapter 4. Global Speech-to-text API Market by Component
Chapter 5. Global Speech-to-text API Market by Vertical
Chapter 6. Global Speech-to-text API Market by Organization Size
Chapter 7. Global Speech-to-text API Market by Deployment Type
Chapter 8. Global Speech-to-text API Market by Application
Chapter 9. Global Speech-to-text API Market by Region
Chapter 10. Company Profiles
Companies Mentioned
- LivePerson, Inc. (VoiceBase, Inc.)
- VoiceCloud LLC
- Speechmatics Ltd.
- IBM Corporation
- Microsoft Corporation
- Google LLC
- Baidu, Inc.
- Twilio, Inc.
- Amazon Web Services, Inc.
- Verint Systems, Inc.
Methodology
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