No content, just for fun.

Thankfully, yet another neat little Yahoo Pipes mashup comes to the rescue. Simply enter the lists’ creator’s user name and the list name, and off you go.

To add a bit of speech tech to this post, here are a few sample lists that you might find interesting:
@die_lautmaler/voicebusiness
@alisohani/machine-learning
@suellewellyn/cunning-linguists
@rachelcotterill/computational-linguistics
(And thanks to people compiling these!)

http://translate.google.com/translate_tts?q=Hello+reader

Just replace “Hello+reader” with any text that you want spoken in your address bar.  Remember to replace spaces with pluses (+).

Some browsers however seem to have problems with the returned audio.  Chrome worked for me, though Internet Explorer is reportedly working as well.

As this is not an official RESTful Google API don’t be surprised if it stops working. Beware that commercial reuse of the output audio is likely also governed by license restrictions.

Update:
Friend Schamai pointed out how this could be employed in a web form. Here’s an example:

Or the corresponding HTML:

<form action="http://translate.google.com/translate_tts">
<input name="q" size="55" value="just saying" />
</form>


I greatly enjoyed this video about a piano-cum-speech-synthesis installation. I also think that this would make a great GarageBand plugin.

You may be new, you may have found me at my old blog (the content of which has already been migrated here.)  This is a fairly content-free post, bidding you a warm welcome here.

Only the best for 2010,

Okko

Have you found any others?

“Innovation usually needs time to steep. Time to turn the idea into something tangible, time to get it to market, time for people to decide they accept it. Speech recognition technology has steeped for a long time”

And concludes:

“Even a digital expert [...] cautions that some people may never be satisfied with the quality of speech recognition technology — thanks to a steady diet of fictional books, movies and television shows featuring machines that understand everything a person says, no matter how sharp the diction or how loud the ambient noise.”

But isn’t this a bit hackneyed? Perhaps by today’s standards a twenty-year steeping period seems long, but this is hardly the case anywhere else in history. And after re-watching 1982′s Blade Runner recently, I actually felt rather optimistic that we are today close to what the movie’s expectations for speech recognition and speaker verification were for 2019. Elsewhere , a similar picture emerges.
The Star Trek ship computer’s speech recognition engine (the year is 2151), while accurate, stills require the push of a button to kick in, rather than listening for the hot word “computer”, a capacity available , if not quite ripe for deployment, today.
Of course, there are the HALs (2001), Marvins (no date), C3P0s (Long long time ago…), whose capacities far exceed that, which we dare dream our mobile phones can one day understand. But here it seems the problem is less about the quality of speech technology – the quality of HAL’s speech synthesis is available today, and Marvin’s characteristic monotone baritone should be easy to do – rather than about the old hard-soft divide in Artificial Intelligence. As long as we use a hard-AI problem, which speech arguably is, to solve soft-AI problems (“find closest pizza service”) we cannot fail to be disappointed.

Oh and of course: this blog is intended to be informative and, unless otherwise specified, makes no claim about the truthfulness of any referenced material. I will do my best to ensure that any of my own opinions can easily be discerned as such. Comments and debate are always welcome.