Speech Recognition - Worldwide

Speech recognition has gained a lot of traction in recent years. The integration of voice assistants and smart speakers into various devices and platforms to provide users with seamless voice-controlled experiences in their homes, cars, and workplaces is a notable trend. Another development is the advancement of automatic speech recognition (ASR) systems using deep learning models. There is also a growing emphasis on developing multilingual and code-switching speech recognition systems to cater to the diverse linguistic needs of global users, enabling more inclusive and accessible voice-based interactions.

The increasing demand for speech recognition technology across various industries, such as healthcare, banking, and retail, is a major growth factor for the speech recognition market. The advancement of AI and machine learning technologies has led to the development of more accurate and reliable speech recognition systems, which is expected to further boost market growth.

The Speech Recognition market is expected to continue its growth at a CAGR of 16.3% from 2023 to 2030. The increasing demand for speech-based virtual assistants and the growing adoption of speech recognition technology in the healthcare industry are expected to be the primary drivers of market growth.

Data coverage: The data encompasses B2B, B2G, and B2C enterprises. Figures are based on the funding values from different industries for the market.

Modeling approach / Market size:Market sizes are determined through a top-down approach with a bottom-up validation, building on a specific rationale for each market. As a basis for evaluating markets, we use annual financial reports, funding data, and third-party data. In addition, we use relevant key market indicators and data from country-specific associations such as GDP, number of internet users, number of secure internet servers, and internet penetration. This data helps us estimate the market size for each country individually.

Forecasts:In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited to forecast digital products and services due to the non-linear growth of technology adoption. The main drivers are the level of digitalization, the number of secure internet servers, and the revenue of the Public Cloud market.

Additional Notes: The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russian-Ukraine war are considered at a country-specific level. The market is updated twice a year. In some cases, the market is updated on an ad-hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development). Data from the Statista Consumer Insights Global survey is weighted for representativeness.