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Let's dig a bit deeper into voice recognition.
As you already know, doctors are busy people. This is never more obvious then when they're dictating their notes. It's understandable they're busy, and as their MT, I can surely forgive them but will the latest voice recognition software be as forgiving as me?
Not likely.
As a transcriptionist you will have typed through background noise, patients moaning, doctors eating their lunch, personal conversations (oops they forgot the recorder was on) and other incomprehensible noise. Not to mention, ESL doctors with heavy accents and very tired ER doctors after a long shift!
At this time there is no voice recognition software which can handle this type of voice recognition. It is impossible for the software to determine actual speech from mistakes in conversation, background noise, heavy accents, etc.
So what does this mean for our future?
Rumors of MTs being out of r a job have been around long before I became an MT. Eight years later, there are still no real advances in this field.
Can voice recognition ever replace transcriptionists?
Sure it can.
If a doctor is willing to sit down and take the sufficient time to train his voice recognition software to recognize his voice and speech patterns (this takes time and is not done automatically), yes it is possible.
If the doctor thereafter dictates very clearly, using proper punctuation in his speech (stopping for periods, pausing for commas) without any background noise or interruptions. Yes, it is possible.
Will the document be 100% accurate?
Remember medical records have to be in compliance with a number of very strict regulations. Most doctors, will not trust voice recognition enough to send these records through without at least a quick glance through.
Even under the best dictating circumstances the report will still need to be proofread and edited. So, yes under the “perfect” circumstances, voice recognition can replace a transcriptionist.
Is it likely? Not unless every physician out there is willing to take the time, energy and ongoing effort to train their voice recognition software and maintain a certain standard of dictation.
I don't see that happening any time soon. Doctors are busy people, remember? ;)
If anything, us MTs should embrace voice recognition and use it as a tool to help us in our MT careers. If applied properly, it can be a time-saving tool. So why not use it for our purposes?
As with any business to stay ahead of the game you have to adapt to change and technology. Learn how to use it to your advantage instead of being frightened by it. That's the only way to stay ahead of the competition…. Voice recognition or otherwise.
Some years ago, when voice recognition software became commercially available, most people expected that the solution had finally arrived. Businesses looked forward to cutting down on transcription costs and everyone who hated typing looked forward to getting rid of their keyboard.
Unfortunately, the reality turned out to be rather different. Voice-to-text technology has been a big let down so far.
The fact is, voice recognition software is easily thrown off track by many different factors. If you don't speak clearly and distinctly, it may not give you the right output. If you try using it in a noisy place, it will fail more often than not. If you have an accent, it may not understand you. Even if you have a bad cold, you'll find that the software may give incorrect results!
In other words, voice recognition software works reasonably well under ideal, laboratory conditions, but not in a typical home or business setting!
Healthcare professionals who attempted to use voice recognition technologies to eliminate transcription services found that they need to “train” the software to function well. That takes a long time and a lot of work. Most wound up continuing to outsource their medical transcription work.
Of course, there are many other types of situations where transcription is needed. Examples include recordings of seminars, teleconferences, interviews and classes that need to be converted to text.
In natural speech, people tend to use lots of “aahs” and “umms” as well as unnecessary phrases like “you know”. Current voice recognition technology is just not capable of filtering out such irrelevant sounds or words.
In addition, people also string together several sentences using “ands”. The software can't break up such speech into meaningful sentences. Nor can it break up speech into meaningful paragraph units the way a transcriptionist can.
And if the recording is filled with background noise, or if more than one person is talking at the same time, the software will not function reliably and consistently.
Maybe sometime in the future someone will invent voice recognition technology that can handle all the above issues. Till then businesses will need to use transcription services, particularly for work like medical transcription, where accuracy is critical.