The 4 Commandments of Intelligent Speech Recognition

The 4 Commands of Professional Speech Recognition We tend to think that speech recognition works by understanding the phonetics behind words and the way a user pronounces those very sounds. Well, that’s “voice” recognition, not “speech” recognition. To be beneficial in a professional document creation approach, a system must be able to interpret what the speaker means, beyond the successful sound-word association. So when you think about it, speech recognition is more about syntax and probability models than sound analysis. This is what Philips calls Intelligent Speech Interpretation, with a fourfold mission that I’m going to baptize the “4 Commandments of Speech Recognition” as opposed to “Voice” Recognition.

Thou shall emulate the capabilities of a good medical Transcriptionist
Just like a medical transcriptionist, the system goes beyond simply typing what was dictated by the physician. The first step is to leave out the ‘um’s and ‘eh’s and ignore the “one lattee and chocolate donut, please” that doesn’t belong to the diagnosis. The system is then able to format and organize text, add section headings, numbering lists and standard blocks of text, and even rephrase sentences when needed.

Thou shall detect and filter background noise
ER physicians will understand what I mean but “background noise…” The challenge for a speech recognition system is to be able to filter out those acoustic events, which have no relevance for the current report. What the system does is comparing those events with known variations in speaker characteristics in order to compensate for deviations. The same rule is applied to dialects, pitch and speed variations, and clarity of pronunciation.

Thou shall not forget that a word is part of a sentence
As described by Marcel Wassink, Managing Director for Philips Speech Recognition Systems,” awareness of what people are likely to say not only helps recognize what they do say, it also helps identify what doesn’t belong, for example, “PET” (photon emission tomography) is more likely in a radiologist’s report than “pet” (an animal kept at home). This awareness is also about knowing the probability of a particular word, given the words used before: the probability of “PET” being followed by “scan” is much higher than it being followed by “food”. Speech recognition thereby offers dedicated dictionaries related to the physician’s speciality that maximizes the recognition of complex profession-related terminology.”

Thou shall think twice
“The system works internally with phonetic representations of words, and rules for the structures of phrases, sentences and documents. Basic representations and rules, along with suitable vocabulary, are initially entered into the system, which then statistically examines large numbers of existing texts. When transcribing a dictation, the system compares the words on hand with these statistics to imply the word, phrase, sentence or document section, and adjust the output accordingly.”

Here are some of the big breakthroughs that changed the speech recognition industry during the past decade, and at the same time, splitting the market in two: the professional market and the consumer market. And indeed, I don’t see how off-the-shelf, basic voice recognition software could be of any help to healthcare users looking to automate the entire documentation workflow. In my opinion, that would be like trying to build a six lane highway using backyard-digging and earth-moving equipment from the Home Depot…

To find out more on Intelligent Speech Interpretation, you can refer to the following white paper or article from the e-Health Insider.


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