The beauty of the network approach

The beauty of the network approach Why does professional speech recognition work so well as opposed to individual applications? Well, let’s think about it. What professional SR does is networking multiple physicians from a same specialty across what they have in common: their language patterns and medical vocabulary. This collegial approach makes a huge difference in itself, since the SR engine will be loaded with vocabulary specific to Pathology or Cardiology for instance. In specialties where medical terminology prevails in the reporting process (i.e.: Radiology as opposed to Psychiatry), great results are achieved right from the start.

Achieving similar results as a consumer would require patience let alone advanced organization skills. Let’s say I’m a soccer fan using speech recognition to comment game strategies, I’d better be part of a networked community sharing the exact same interest and using speech recognition for the exact same purpose…

Now, what about individual pronunciations? How does the engine work this out? Once a “speech recognized” report has been corrected and signed off, the speech recognition engine initiates what is probably the most important phase of all; it is called Adaptation. During adaptation, the SR engine makes all the required adjustment by comparing the recognized -draft- report and its corrected -final- version, matching a specific pronunciation with a specific word here, collecting an unknown word to be added to the lexicon there. And because this lexicon is shared with other users in the department, every new word is automatically and immediately made available to everyone else on the network. That’s nothing more than the whole “United we stand, divided we fall” concept at work.

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