The market for voice and speech recognition globally was valued at USD 14.22 billion in 2021 and is anticipated to reach USD 80.25 billion in 2030 growing at a compound annual growth rate (CAGR) of 15.23% from 2022 to 2030.
Natural language processing has found a number of important applications, one of which is speech recognition. Communication between human beings is mostly accomplished via the use of speech. People communicate their concepts and ideas to one another using a particular language. Computers are able to comprehend human language because to advancements in speech and voice recognition. The method of speech and voice recognition involves extracting the features of speech and voice and then categorising those traits based on how they match up with a dataset that has been previously recorded.
The process of recognising words or phrases and converting them into a format that can be read by a machine is known as automated speech and voice recognition. This process is also referred to as automatic speech recognition and voice recognition. By swapping the audio and text in the digital format, users would be able to manage the devices with their speech and voice rather than by utilising traditional input devices such as a keyboard, mouse, and other similar devices.
The expansion of the speech and recognition market will be fueled by an increase in the demand for voice and speech biometric systems as well as an increase in the usage of voice-based authentication in mobile apps. The need for speech and voice recognition systems would be driven by the increased usage of superior technologies such as AI, IoT, and machine learning. The speech and recognition market is expected to be driven in the next years by technologies such as voice recognition, which will be employed in developing technologies such as self-driving and autonomous automobiles, as well as speech and voice recognition in robots.
The market is to be driven by emerging technical breakthroughs as well as the development of deep learning and neural network techniques. Classification algorithms are typically utilised in traditional speech and voice recognition systems in order to get the desired result. In various facets of speech and voice recognition, such as isolated word identification, audio-visual speech recognition, digital speaker recognition, and speaker adaptability, deep learning and neural networks have emerged as useful tools. The development of automated speech recognition (ASR) systems has been made possible by recent advances in deep learning and neural network methods.
The purchasing habits of consumers are changing in both developed and emerging nations. From the comfort of their homes, customers may browse items, inquire about prices and features, and even get tailored suggestions based on past purchases. With the use of voice assistants, this experience may be made much more seamless and interactive. When buying online, 41% of customers say a voice assistant is preferable to a website or app because it helps them to automate their regular purchasing activities.
The largest portion of the worldwide revenue in 2021—more than 33.00 percent—was generated in North America. The region is anticipated to continue to grow at a constant CAGR and hold the leading market position during the projected period.
Due to the growing trend of linked devices in automotive and home automation, speech & voice recognition technologies are anticipated to have greater usage in the consumer electronics and retail industries in Europe. In China, Japan, and Singapore, there is a rising need for speech and voice recognition, which is anticipated to drive market expansion throughout the Asia Pacific region.
Few internationally renowned companies, including Apple (US), Microsoft (US), IBM (US), Alphabet (US), Amazon (US), Baidu (China), iFlytek (China), SESTEK (Turkey), speak2web (US), and Verint, dominate the speech and voice recognition business (US).
Verint introduced its low-code conversational AI product, the Verint Virtual Assistant (IVA), in April 2021. IVA can quickly transform the current conversation data into automated self-service experiences. It enables business experts to swiftly create a chatbot that is ready for production to divert calls and assist clients. Businesses may increase capabilities throughout the organisation with Verint IVA's limitless voice and digital intelligence.
In order to incorporate ambient clinical intelligence (ACI) into Microsoft Teams and scale virtual consultations targeted at improving physician wellbeing and patient health outcomes, Microsoft and Nuance Communications announced Nuance Dragon Ambient eXperience (DAX) in September 2020.
An automated voice recognition service called Amazon Transcribe Medical was launched by Amazon Web Services in December 2019. It will assist developers in adding medical dictation and documentation to their products.
Watson Assistant, a smart enterprise speech recognition and assistant system driven by AI, cloud, and IoT, was introduced by IBM in March 2018.