It is not the voice recognition capability, but the "semantic recognition capability" that impresses the most. For example, here are three simple questions that Siri can answer (from the "Let's talk iPhone" event):
1) “What is the weather like today?” (Siri answered: “Here’s the forecast for today”),
2) “What is the hourly forecast?” (Siri answered: “Here is the weather for today”), and
3) “Do I need an raincoat today?” (Siri answered: “It sure looks like rain today”).
The first two are probably easy enough to achieve just with sophisticated voice recognition, but the third is a lot more tricky. Siri has to know that in asking about clothing, you are "really" asking about weather. But how does she know that?
While the details of Siri's technology are proprietary, Tom Gruber, one of Siri's creators, gives us some brilliant insights in this keynote address. These are the essential points:
- Task oriented
- Context is king
- Precise and limited information space
- Semantic auto completion / snap to grid rather than general intelligence
The key is precise modeling with semantic technologies in a context aware mobile platform. Mobilesemantics has come of age!