Automatic Speech Recognition Market Size, Share, Competitive Landscape and Trend Analysis Report, by Component, by Deployment Mode, by Organization Size, by Application, by Industry Vertical : Global Opportunity Analysis and Industry Forecast, 2022-2032

Automatic speech recognition enables a computer to recognize and transcribe spoken words into written text. Automatic speech recognition systems are used in various applications, including voice-to-text transcription for phone systems, voice assistants such as apple's Siri and Amazon's alexa, and real-time transcription of lectures and meetings. This technology is based on machine learning algorithms, which are trained on large datasets of speech samples. Also, these systems uses algorithms to analyze voice of a person, recognize specific words and phrases, and convert them into written text.
The adoption of automatic speech recognition technology is increasing rapidly since it becomes more prevalent and advanced in understanding and processing human speech. Some of the major players in the market include IBM, Microsoft, Nuance Communications, and Google. These companies offer a broad range of automatic speech recognition products and services, including on-premise software, cloud-based services, and integrated automatic speech recognition solutions for specific industries.
Increase in adoption of voice-based interaction has led the growth of the automatic speech recognition market. Furthermore, rise in demand for real-time transcription in industries such as education and healthcare to provide real-time transcription of lectures, meetings, and patient notes further propels the growth of the automatic speech recognition market. Moreover, the rise in demand for speech recognition technology in the transportation industry for tasks such as voice-based navigation and voice-based control of in-vehicle systems also contribute toward growth of the automatic speech recognition market. In addition, rise in development of natural voice assistant technology by key players further fuels the growth of automatic speech recognition market. For instance, Qualcomm has developed a natural voice recognition system that enables drivers and passengers to interact using voice commands in cars. This system allow drivers to control various aspects of cars, such as adjusting the seat position or making purchases, without the need to use touch inputs. Hence, this technology aims to make it more convenient and user-friendly for drivers and passengers to interact with the car's systems. Such strategic developments or advancements will contribute in significant expansion of automatic speech recognition market over the forecast period.
One of the main challenges faced by the automatic speech recognition market is the inaccurate transcription of different accents and languages. However, automatic speech recognition systems may sometimes not transcribe spoken words accurately due to lack of lingual training and low data reliability on ASR technology. Furthermore, handling background noise and overlapping speech is also a major obstacle in ASR technology, which further limits the market growth around the world. This is attributed to the fact that automatic speech recognition systems typically face issues while transcribing spoken words accurately in noisy environments or when multiple people are speaking simultaneously. Integrating automatic speech recognition systems with other systems can also be challenging, owing to differences in data formats and protocols. These aforementioned factors are expected to inhibit the market growth.
There is a rise in demand for automatic speech recognition products and services that can handle multiple languages as more and more businesses and organizations operate globally and must be able to interact with customers and clients in various languages. Companies that develop multi-lingual automatic speech recognition systems are expected to have a significant advantage in this market. For instance, Google developed its cloud speech-to-text API, which supports a wide range of languages and accents, including English, Spanish, French, German, and Chinese. Such strategic developments by key players will create numerous opportunities for the growth of global market.
Surge in integration of other technologies, such as natural language processing and machine learning, with automatic speech recognition is expected to present significant opportunities for growth of automatic speech recognition market. Natural language processing allows automatic speech recognition systems to understand and respond to interpret meaning of spoken words rather than just transcribing them. In contrast, machine learning allows automatic speech recognition systems to improve their accuracy over time by learning from their mistakes. Companies that develop integrated solutions, which combine automatic speech recognition with natural language processing and machine learning are expected to be well-positioned to take advantage of these opportunities.
By component: the automatic speech recognition market is segmented into solutions and services. Solutions refer to hardware and software components used to enable speech recognition functionality. These solutions may include microphones, speakers, and other hardware devices, as well as automatic speech recognition software used to analyze and transcribe spoken words. Dragon professional individual software, offered by Nuance Communications, allows users to transcribe spoken words into text on a computer, and dragon anywhere, a mobile app that enables users to dictate text on their mobile devices.
Automatic speech recognition services refer to professional services that automatic speech recognition companies provide to support deployment and use of automatic speech recognition solutions. These services may include installation, training, maintenance, and support for automatic speech recognition systems. It may further include transcription and translation services and consulting services to help businesses and organizations to implement automatic speech recognition technology effectively. For instance, Verbit provides transcription and captioning services for educational institutions, using both human transcribers and AI-powered transcription technology.
By deployment mode: the automatic speech recognition market is divided into on-premise and cloud. On-premise automatic speech recognition solutions are installed and run on user's own servers or local devices, while cloud-based automatic speech recognition solutions are accessed over the internet and do not required users to invest in their own infrastructure. On-premise solutions offer more control but may be more expensive and require more maintenance, while cloud-based solutions are more scalable and flexible, with lower upfront costs.
By organization size: the automatic speech recognition market is categorized into are large enterprises and small & medium enterprises (SMEs). Large enterprises, which are typically defined as organizations with over 1,000 employees, may have more resources and a greater need for automatic speech recognition technology, while SMEs, which are typically defined as organizations with fewer than 1,000 employees, may have more modest needs and budgets for automatic speech recognition technology. Automatic speech recognition solutions and services may be tailored to meet specific needs and requirements of different organizations.
By application: the automatic speech recognition market is categorized into risk & compliance management, fraud detection & prevention, customer management, content transcription, contact center management, and others. Automatic speech recognition technology can be used in a range of industries, such as finance, insurance, customer service, and healthcare to support functions such as risk assessment, fraud prevention, customer interaction, transcription, and contact center operations.
By industry vertical: the automatic speech recognition market is categorized into BFSI, IT & telecom, media & entertainment, healthcare & life sciences, retail & e-commerce, government & defense, education, and others.
By region: the automatic speech recognition market is segmented into North America, Europe, Asia Pacific, Latin America, the middle east, and Africa. North America is expected to dominate the automatic speech recognition market, owing to presence of a large number of automatic speech recognition vendors and high adoption rate of automatic speech recognition technology in various sectors, such as healthcare, education, and customer service. Europe is expected to follow North America, owing to presence of a large number of automatic speech recognition vendors and adoption of automatic speech recognition technology in various sectors, such as finance, insurance, and customer service.
Key players profiled in the automatic speech recognition market are Amazon Web Services, Inc., Apple Inc., Baidu Inc., Google LLC, IBM Corporation, Microsoft Corporation, Nuance communications Inc., Soundhound ai Inc., Verbit Software Ltd., and Verint systems Inc. Major players have adopted product launch and acquisition as key developmental strategies to improve the product portfolio of the automatic speech recognition market.

  Automatic Speech Recognition Market Report Highlights