Researchers at MIT have developed a new approach to training speech recognition systems that does not depend on transcriptions – as is the current model. Instead, their system analyses correspondences between images and spoken descriptions of those images, as captured in a large collection of audio recordings. The system then learns a mapping between acoustic features of the recordings correlated with image characteristics. Traditionally speech recognition systems such as those that convert speech to text on smartphones are the result of machine learning systems that go over many thousands of utterances and their transcriptions to learn a mapping between acoustic features and words. While this method works quite well, the requirement of professional grade transcription is costly and time-consuming.

Global Speech Recognition Market is expected to grow with market size of US $13 billion by 2022. Growing mobile banking application and adoption of mobile- and cloud-based computer technology is driving the Speech Recognition Market. The growing adoption of automated and smart applications in consumer electronics and healthcare industries act as the major contributor for the growth of the speech recognition market during the forecasted period. Taste the market data and market information presented through more than 50 market data tables and figures spread over 110 numbers of pages of the project report. Market Research Future has predicted that this market will be dominated by North America throughout the forecast period.

Daniel Faggella is founder of TechEmergence, a news and advice website for entrepreneurs and investors interested in the intersection of technology and the mind. Speech recognition technology has been around for more than half a decade, though the early uses of speech recognition -- like voice dialing or desktop dictation -- certainly don't seem as sexy as today's burgeoning virtual agents or smart home devices. If you've been following the speech recognition technology market for any length of time, you know that a slew of significant players emerged on the scene about six years ago, including Google, Apple, Amazon and Microsoft (in a brief search, I counted 26 U.S.-based companies developing speech recognition technology). Since that time, the biggest tech trend setters in the world have been picking up speed and setting new benchmarks in a growing field, with Google recently providing open access to its new enterprise-level speech recognition API. While Google certainly seems to have the current edge in the market after substantial investments in machine learning systems over the past couple of years, the tech giant may yet have a potential Achilles' heel in owning an important segment of the global market -- lack of access to China.