There is something about the voice recognition algorithm that uses later words to understand what you were saying earlier. For example, whenever I say, "Show me pictures of humpback whales" - GoogleVoice starts off with "Show me pictures of home" and then when I add the word "back", it corrects home to be hump.
To some degree, that's probably how the human brain works. If you say out loud "Show me pictures of Hump" and then just stop, it really does sound pretty close to "Show me pictures of home"
I am very, very impressed on how much better than Siri the voice recognition is in terms of speed and responsiveness. And, it works just fine on my iPhone 4, where Siri isn't an option.
The standard machine learning approach for doing exactly what you describe is to use a conditional random field. I don't think wikipedia has a great page on it , but check out http://en.wikipedia.org/wiki/Conditional_random_field for a jumping place.
CRFs are used in places like voice and images where recognition or decoding of a segment logically depends on the pieces near it.
For clarification, it's much more likely a Hidden Markov Model. Most speech recognition algorithms use some form of Baysesain probability model, HMM being the most commonly used e.g. Sphinx CMU.
Wow. I haven't tested IOS6 with SIRI, but when it was Google Voice v/s Siri on IOS 5.1.1 - there was no comparison. Google voice won hands down. Even in a noisy environment.
I've just bought a second hand iPhone 4s that will be upgraded to IOS6 so I can compare for myself. Until a month ago, Google was easily king of the hill.
To some degree, that's probably how the human brain works. If you say out loud "Show me pictures of Hump" and then just stop, it really does sound pretty close to "Show me pictures of home"
I am very, very impressed on how much better than Siri the voice recognition is in terms of speed and responsiveness. And, it works just fine on my iPhone 4, where Siri isn't an option.