Speech-to-Text API Market Insight

Speech-to-text application programming interface is an API that allows use of speech synthesis and speech recognition within various devices and applications. Speech-to-text API is an interdisciplinary subfield of computational linguistics that develops technologies and methodologies, which enable translation and recognition of oral language into text by computer. This is also known as Automatic Speech Recognition (ASR) or Speech-to-text (STT). It includes research and knowledge in electrical engineering, computer science, and linguistics.Currently, the field has benefited from advances in deep learning and big data. The advances are demonstrated not only by a rapid increase in number of academic papers published in the field, but by the worldwide industry adoption of a variety of deep learning methods in designing and implementing speech recognition systems.

Speech-to-Text API Market Scope and Structure Analysis:

Impact of COVID-19 onSpeech-to-Text API Market:

• All businesses are facing risks including shifts in customer touchpoints, supply chain disruptions, unavailability of critical resources, and gaps in business continuity protocols.
• Shifts from physical to digital purchasing has led to surge in transaction volumes and precipitous decline in demand.
• To respond to immediate business needs in dynamic environment reporting, monitoring and decision-making with real time data is necessary.
• There are workforce productivity challenges,as employees working remotely, associated with connectivity and security.

Top impacting factors: Market Scenario Analysis, Trends, Drivers, and Impact Analysis

Increase in adoption of smart speakers and phones among individuals across the globe is a major factor that drives the market growth. This is attributed to speech-to-text API feature that recognizes a human voice and follows command without the need for human interference. Moreover, rise in inclination toward voice-based technology products and solutions among industries and individuals is also a factor expected to propel the demand for speech-to-text API software in the coming years.However, lack of multilingual support that transcribe audio from multi-source is a factor that hinders the speech-to-text API market growth. Furthermore, on-going R&D for innovative speech-to-text solutions for disabled population is expected to create significant revenue growth opportunities for players operating in the speech-to-text API market. In addition, growth inspeech analytics and recognition technologies across industry verticals is expected to garner high revenue growth in the coming years.

Rise in adoption of smart speakers and phones

With increase in adoption of digital voice assistants, the market is expected to witness high growth rate as it operates as an interface between devices and human. This has further increased the speech-to-text API demand among consumer technology and repair ecosystem to help its end userswith hand free experience.Hence, advancements in electronics with technology, coupled with rise incustomer demand for self-services further boosts growth of the market.

The primary example of speech-to-text API is a chatbot. In addition, many retrofit industries are adopting initiatives for thedevelopment of self-learning chatbots that help them to deliver a more human-like conversational experience, whichpropels the market growth at a significant rate. This is attributed to cost saving benefit that also helps in minimizing or eliminating the need forhuman intervention and improves customer experience.

Moreover, major smart phone users prefer voice-based search API’s as they are easy to use and accessible. In addition, voice-based products known as intelligent virtual assistance such as Amazon’s voice technology product, Alexa, have raised its sales at a significant rate, which, in turn, is expected to drive the growth of the market.

Transcribing audio from multi channels

A smart virtual assistant is mostly depended on recognition side. Technology users prefer for quick responsive system. A smart virtual assistant uses recognition time, which can change from few seconds to few hours to days depending on the underlying complex software, abilities of integrated hardware, strength, and speed of the internet connectivity and adjusts itself to user’s speech patterns. This factor is expected to hamper the growth of market to a certain extent. Another barrier proven in the smart virtual assistant is the extra noise on voice activated systems, which have negative impact on speech recognition devices and is expected to further hamper the market growth.

Key segments covered:

Key benefits of the report:

• This study presents analytical depiction of the globalspeech-to-textAPI industry along with the current trends and future estimations to determine the imminent investment pockets.
• The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the globalspeech-to-textAPI market share.
• The current market is quantitatively analyzed from 2020 to 2027 to highlight market growth scenario.
• Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.
• The report provides a detailed market analysis based on the present and future competitive intensity of the market.