Speech-to-text API - Global Market Outlook (2018-2027)
According to Stratistics MRC, the Global Speech-to-text API Market is accounted for $1.32 billion in 2018 and is expected to reach $6.63 billion by 2027 growing at a CAGR of 20%. Increasing adoption of smart speakers and mobile phones and stringent administrative and consistence is likely to boost the growth of the market. However, Transcribing audio from multi-channels and its exactness is likely to hamper the profit boundaries.
Speech-to-text API is an interdisciplinary subfield of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the linguistics, computer science, and electrical engineering fields. From the technology perspective, Speech-to-text API has a long history with several waves of major innovations. Most recently, the field has benefited from advances in deep learning and big data. The advances are evidenced not only by the surge of academic papers published in the field, but more importantly by the worldwide industry adoption of a variety of deep learning methods in designing and deploying speech recognition systems.
Based on the organization size, the Small and Medium-sized Enterprises segment is expected to grow at a higher CAGR during the forecast period. Due to the high availability of cost-effective cloud solutions, speech-to-text API software and services are expected to witness a prominent growth rate among SMEs during the forecast period. Moreover, easy availability of speech-to-text API solutions as well as real-time support services are factors projected to drive the demand for such solutions across SMEs.
By geography, North America is expected to hold the largest market size in the global speech-to-text API market. North America is the most significant revenue contributor to the global speech-to-text API market. The region is witnessing significant developments in the market. In North America, the high growth rate can be attributed to the increasing use of the big data technology, growing amount of data across verticals, and increasing investments by companies in real-time analytics
Some of the key players in the Speech-to-text API market include Voicebase, Voci, Vocapia Research, Verint, Twilio, Speechmatics, Otter AI, Nuance Communications, Nexmo, Microsoft, iFLYTEK, IBM, Govivace, Google, GL Communications, Facebook, Deepgram, Baidu and AWS.
• Other Components
Deployment Modes Covered:
• Other Development Modes
Organization Sizes Covered:
• Small and Medium-Sized Enterprises
• Large Enterprises
• Other Organization Sizes
• Content Transcription
• Customer Management
• Fraud Detection and Prevention
• Risk and Compliance Management
• Other Applications
End Users Covered:
• Travel and Hospitality
• Telecommunications and IT
• Retail and Ecommerce
• Media and Entertainment
• Government and Defense
• Banking, Financial Services, and Insurance
• Other End Users
• North America
o Rest of Europe
• Asia Pacific
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2017, 2018, 2019, 2023 and 2027
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic analysis: Drivers and Constraints, Product/Technology Analysis, Porter’s five forces analysis, SWOT analysis etc.
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
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