Naturally Speaking

We used voice to text, text to voice and semantic data analysis successfully on two products for Pearson Education a few years ago — AMP Reading and Quick Reads — which rocked, technically and commercially. But successful though they were, as products for middle-school kids there was professional but not personal relevance. Finally, these technologies are starting to show up in consumer products, two of which are in heavy rotation on my iPhone.

I’m totally hooked on the mobile version of Dragon Naturally Speaking. At first it was like having an assistant with a notepad always available, capturing musings, insights or solutions that came to mind in the supermarket checkout line. The more I used it and learned to trust the accuracy — 99% spot on in my experience — the more I’ve been using it in the office as a dictation device. Very valuable, even more so because (at least for now) it’s free in the App store.

Now Siri, a venture funded startup, has raised the bar with their personal assistant. After nearly a year in development and $24 million in venture capital, Siri is brings a conversational interface to the iPhone which allows you to ask it to perform tasks for you, such as find a French restaurant nearby and book a table, look up movie listings, order a taxi, or look up the phone number and address of a local business.

You simply speak into the phone with a request, it turns your speech to text and pushes your request out to an appropriate service on the Web, then not only attempts to bring you back the appropriate information based on context, time of day, and your location, but with your permission can go ahead and make reservations or buy tickets as well.

How cool is that? Well, not so fast, but it’s getting there. Compared with Dragon Dictation I’m finding Siri is not as spot-on in its results, but since it uses the Dragon technology and they have deep pockets to continue development I’d wager it’s only a matter of time before they nail it. Read more on Mashable or  TechCrunch or peep this:

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