Voice recognition is getting better by the day and may be the future of communications. Many people find it more convenient to speak while typing.
However, there are problems with creating voice recognition software that must be dealt with before this technology can become as ubiquitous as typing.
Why Is It So Hard to Make Voice Recognition Software?
Voice recognition software is a challenge to design because this software must think like a human being.
Most people can make sense of a variety of accents, speakers who lack good diction habits, and unfamiliar idioms. In addition, we are used to “filling in blanks” based on previous experiences, using information from prior communications.
Voice recognition software programs need to work in similar ways. Creating a program or algorithm that is as intuitive and teachable as a human brain, however, presents its own challenges.
What Are Some of the Challenges?
One key challenge of designing effective voice recognition software is that even medical researchers don’t entirely understand how the human brain processes speech from a spoken word. It is a complex system that is difficult to “scale” to a program.
First and foremost, the program needs to be able to continuously train and retrain itself.
Another challenge is that computer programs require “normalized data,” or a standard voice. It is difficult to select a “normal” voice, accent, vocabulary, and diction.
In addition, voice recognition software needs to be able to sense context and fill in blanks based on this context, similar to the way humans understand speech.
While software engineers certainly can accomplish this task, they may have more difficulty fitting the large and complex amount of information into a reasonable amount of data.
What Solutions Are Being Implemented to Improve Voice Recognition Software?
There are several solutions that are being implemented to improve voice recognition software.
First, the voice recognition algorithms are being programmed to respond to the vocal and speech patterns of their user. The same way autocorrect programs adjust recommendations based on their user’s former behavior, voice recognition software is increasingly being programmed to customize itself to users.
Second, technologies are increasingly being fit into smaller amounts of data, which resolves the key issue of data size. As technology advances, voice recognition software likely will require less data, while laptops and other devices will continue to offer ever-larger data packages.
Third, artificial intelligence is becoming less of a science fiction story and more of a programming reality. More and more programs allow software programs to act intuitively and predictively, an advance that will surely lead to better voice recognition software.
While the issues inherent in designing voice recognition software are complex, researchers and programmers are slowly dealing with them. The result is that every generation of voice recognition software is significantly improved from the prior version.
This technology is being used in a wider range of contexts as it becomes more reliable and more user-friendly. Soon voice recognition software will be as reliable as text with even more benefits.