The powerful mobile computing platforms of today ‘SmartPhones‘ have so little in common with “phones” of yesteryear and in fact with the introduction of Tablet Devices into the mix, we should start calling them Converged Mobile Devices. While processor, battery and software technologies have taken leaps forward over the past couple of years, there is still one thing small mobile devices can’t be. Big. And herein lies the rub, because a lot of the perceived limitations imposed by form factor are really just side effects of trying to make CMD’s act like little tiny laptops. Leveraging speech recognition in mobile business applications could be one way to enhance the power and functionality of mobile devices.
Many mobile devices already run speech recognition programs that allow users to use voice features for navigation and search. In fact there are a number of mature applications that enable voice interaction with mobile devices. And there are plenty of practical reasons for enterprise mobile solution providers to start looking into speech based UIs sooner rather than later. For starters, forty seven states have enacted distracted driving laws, some with very stiff penalties. They have good reason. A recent CDC survey reports that 52% of U.S. drivers ages 18-29 admit texting or e-mailing while driving at least once in the last 30 days, and more than a quarter report texting or e-mailing “regularly” or “fairly often” while driving. So first off, building speech based UIs into apps designed for workers who spend a lot of time behind the wheel is an easy way to help encourage compliance with corporate distracted driving policies.
There are other reasons that speech based interfaces make really good sense on mobile devices, and these have to do with the science of speech processing and the kind of use cases in which it works best.
Historically, one of the strong application areas for speech recognition has been in healthcare settings, and this is still true. Most speech UI equipped healthcare applications have been successful in large part because a speech recognition engine functions best after it learns a particular person’s (or limited group of people’s) vocabulary, intonation and accent. Individualized medical charting systems and personal mobile devices have something in common which tends to eliminate this problem: They are virtually always listening to the same person, so recognition becomes accurate quickly. In addition, mobile phones are optimal speech recognition hardware right out of the box.
For certain kinds of business applications, mobile apps with speech recognition can provide a more efficient way to perform certain kinds of mobile tasks.
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