Speech-to-text API Market Trends, Regional Study, Size, Share, Industry Profit Growth Analysis

The market for Speech-to-text API is projected to grow from USD 2.2 billion in 2021 to USD 5.4 billion by 2026; it is expected to grow at a CAGR of 19.2% during 2021-2026.

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The COVID-19 pandemic has impacted trading activities across regions. It has had a moderate impact on all elements of the technology sector. The hardware business is predicted to be the most impacted in the IT industry. Owing to the slowdown of hardware supply and reduced manufacturing capacity, the IT infrastructure growth has slowed down. Businesses providing solutions and services are also expected to slow down for a short period. However, the adoption of collaborative applications, analytics, security solutions, and AI is set to increase in the remaining part of the year. Verticals such as manufacturing, retail, and energy and utilities have witnessed a moderate slowdown, whereas BFSI, government, and healthcare and life sciences verticals have witnessed a minimal impact. Moreover, with recovery, global ICT spending is estimated to increase by approx. 3.5%-4.5% from 2020 to 2021. The impact of COVID-19 is believed to be short-term; however, it may have a significant effect on businesses and forecasts to a significant extent for a minimum of 8-12 months.

During the pandemic, many companies experienced a significant increase in pressure from customers, while their number of available employees decreased. Many contact centers were unable to cope with demand or closed because of lockdown restrictions, leading to long delays in customer service queries, which significantly affected the customer experience. As businesses develop a more strategic approach that delivers resilience into operations through the flexibility and scalability while at the same time working to improve operational efficiencies, so speech-to-text API is rising to the forefront of technology enablers.

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Data analytics application builders are seeking medical speech recognition capabilities that help them efficiently and accurately transcribe video and audio containing COVID-19 terminology into text for downstream analytics. For instance, AWS offers Amazon Transcribe Medical, which is a fully managed speech recognition (ASR) service that makes it easy to add medical speech-to-text capabilities to any application. Powered by deep learning, the service offers a ready-to-use medical speech recognition model that users can integrate into a variety of voice applications in the healthcare and life sciences domain. Users can use the custom vocabulary feature to accurately transcribe more specific medical terminologies, such as medicine names, product brands, medical procedures, illnesses, or COVID-19-related terminology.

The services segment to hold higher CAGR during the forecast period

Based on components, the market size of the software segment is expected to hold a larger market share in 2021, while the services segment is projected to grow at a higher CAGR during the forecast period. This can be attributed to the need for determining the time and cost required to install the API/software tools that require fully managed speech-to-text API services. The high growth is attributed to the higher adoption of speech-to-text API solutions across key verticals, such as BFSI, media and entertainment, and retail and eCommerce.

The cloud segment to hold the larger market size during the forecast period

Based on deployment mode the speech-to-text API market is bifurcated into on-premises and cloud. The market size and CAGR of the cloud segment are estimated to be higher than the on-premises segment during the forecast period. The cloud technology benefits of easy deployment and minimal capital requirement facilitate the adoption of the cloud deployment model. The adoption of cloud-based speech-to-text API solutions is expected to be supported by the COVID-19 pandemic, as lockdowns and social distancing practices are encouraging companies to move to cloud solutions that can be managed remotely. The increasing demand for scalable, easy-to-use, and cost-effective speech-to-text API solutions is expected to accelerate the growth of the cloud segment in the speech-to-text API market.

The large enterprises segment to hold a larger market size during the forecast period

The large enterprises segment is estimated to hold a larger market share in 2021. The growth of the segment is due to increased competition in large enterprises from budding SMEs. Owing to the availability of cost-effective cloud solutions, speech-to-text API solutions and services are expected to witness a prominent growth rate among SMEs during the forecast period.

Healthcare and life sciences vertical is to have the highest CAGR during the forecast period

The healthcare and life sciences segment is projected to grow at the highest CAGR during the forecast period. Speech-to-text API helps financial institutions effortlessly connect with customers to provide an enhanced customer experience. The need for rapid diagnosis, healthcare data analysis, and better patient care is expected to drive the growth of the healthcare and life sciences vertical in the APAC region.

North America to hold the largest market share during the forecast period

In North America is expected to hold the largest market size in 2021. In North America, speech-to-text API/software tools and services are highly effective in most organizations due to the increasing need to extract meaningful insights from voice data to enhance user experience. APAC is expected to hold the largest CAGR during the forecast period, while Latin America and MEA are slowly picking up speech-to-text API due to its benefits for various industries to get user insights.

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Key players offering Speech-to-text API market. The major vendors covered Google (US), Microsoft (US), AWS (US), IBM (US), Verint (US), Baidu (China), Twilio (US), Speechmatics (UK), VoiceCloud (US), VoiceBase (US), Voci (US), Kasisto (US), Nexmo (US), Contus (India), GoVivace (US), GL Communications (US), Wit.ai (US), VoxSciences (US), Rev (US), Vocapia Research (France), Deepgram (US), Otter.ai (US), AssemblyAI (US), Verbit (US), Behavioral Signals (US), Chorus.ai (US), Gnani.ai (India), Sayint.ai (India), and Amberscript (Netherlands).

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