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I wonder how much has really been invested in voice recognition. Voice recognition tech would come in handy when interacting with automated homes, appliances, cell phones, etc. So to close the master bed room shades say "Upstairs Master Shades Close". The software will be looking for a small group of voice commands for the first word like "All, Upstairs, Downstairs and Basement". This first command tells the computer which floor to activate. On each floor there is a series of other voice commands which would be the room list like "Bath, Childrens, Guest, Master, Closet and Hallway". So with each command you get more and more specific. Far from conversational speech but it is logical and direct. No bullshit = No error. Probably would not have to voice train with a minimal voice interface like this. Now in terms of voice transcription like the Google Youtube video thingy, I assume you'd need faster processors and much more detailed thorough programs to determine the difference between the vocal versions of 'site' and 'sight'. That's context recognition. It'd have to be able to understand context by 'keyword' collection and relationships. Semantic web comes into play here and that is not yet here. Also advanced machine learning, AI has to be present. Vast databases will be called upon. So much faster processors will be needed. But why screw with voice recognition when thought recognition is the real aim. Its much more elegant and minimal than voice. Less waste and confusion. Along with thought comes vision. So future computer interfaces will be purely visual & mental. What needs to happen is a full merger between the fields of synthetic biology, nano-technology, AI, machine learning, computer hardware, etc. We can really start to see that the lines in some cases are beginning to blur. Word.
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Jul 1, 2010