Okko in Speech

The old maxim “I need more data” should be familiar to anyone who has ever tried to wrestle with language technology issues, attempted speech application tuning or delved into any statistical approach to an AI-related problem. Google moved into the speech world last year with GOOG-411, a speech recognition driven directory assistance application (you say what you are looking for and where, it returns suitable businesses and connects you to the one you want or sends you details in an SMS).
Like all (well, most) other Google services, GOOG-411 is free for the end-user. As such, the basic business model (collect data, turn data into cash) applies. This was recently confirmed in interview by Marissa Mayer, Google’s VP of Search Products and User Experience:

Whether or not free-411 is a profitable business unto itself is yet to be seen. I myself am somewhat skeptical. The reason we really did it is because we need to build a great speech-to-text model … that we can use for all kinds of different things, including video search.

Google thus couples statistical AI and its general data-driven approach to everything in a novel way. In doing so, Google may find itself in a catch-up race with the ilk of Nuance, Loquendo IBM, or Telisma, whose stronghold on speech recognition technology comes, in part, from having aggregated speech and language databases through data collection during professional services projects.
What’s new in Google’s approach, however, is the convergence of the dual role that data plays in AI and in the overall service-driven business model. Google will presumably not be content to bootstrap a pattern matching engine to sell licenses like the technology companies above. More interestingly to follow will be the range of services Google can spin using this technology (context sensitive video advertising, audio indexing, IVR hosting) which are more befitting of their overall company strategy.
Unsurprisingly, Mayer goes on to claim that Google isn’t working on ways out of the world of brute-force data-driven algorithms:

People should be able to ask questions, and we should understand their meaning, or they should be able to talk about things at a conceptual level. … A lot of people will turn to things like the semantic Web as a possible answer to that. But what we’re seeing actually is that with a lot of data, you ultimately see things that seem intelligent even though they’re done through brute force.

User privacy advocates may also have a thought or two on this new dimension of data collection, as Google is beginning to loose the “conventionally trustworthy” image it held amongst many over the past years. Fortunately the ways in which speech data is commonly used to train pattern matching models involves very little in the ways of privacy infringement.
Happy data collecting!

I stumbled across some “traditional” news bits this week for speech and language technologies, representing most of the major and a few interesting minor market players . Yahoo is offering some kind of NLP-driven structured search for e-commerce solutions starting next year. A new bundled automatic translation software with automatic learning capabilities was announced by across Systems GmbH and Language Weaver. Loquendo is sponsoring a speech-for-in-car-navigation industry event. Persay, maker of voice authentication software, is shipping solutions securing Planet Payment’s voice-enabled payment processing. Lastly Nuance, continuing its acquisition spree, buys Viecore, a contact-center integration consulting company, indicating a clear focus on strengthening its traditional speech and telephony market position.

Recently I stumbled across and blogged about VoiceGlue, an integration of various GPL-licensed pieces of software, providing full IVR capabilities (including rudimentary speech synthesis but not recognition.) Well, last night, together with Christoph, I finally had a stab at it myself.
Our test setup involved running Fedora 9 virtualized in Mac OS X. Our Fedora installation was missing a few pieces of software beyond the indicated prerequisites, but after about an hour everything was under way.
The trickiest bit proved to be building various modules required for the XML parser (I presume needed later for VoiceGlue-customized DTMF grammar parser.) For some reason CPAN’s console kept conking out on us (claiming inexplicably missing/unbuildable prereqs), so after wrestling with that for some time, we decided to manually build all the modules ourself (hoorah, makefiles).
This worked like a charm, though we hit a snag with the Module::Build perl module, which required C_Support, which in turn required another perl module (ExtUtils-CBuilders), not mentioned in any documentation (scant across the board, though that’s half the fun, isn’t it).
After that, the VoiceGlue installation completed swiftly and all services started running after a minimal bit of configuration.
Next week we’ll be back with some test calls and our first impressions. In the meanwhile we’ll keep our eyes peeled for ASR integration (LumenVox/Sphinx), which will make this a truly valuable stab at open sourcing some of the most expensive carrier-grade technology out there.

Today on the WWW:

• Nuance announces voice search framework, based on directory assistance solutions portfolio.
• Epson releases speech synthesis chip, powered by Fonix engine, allows mixed output of synthesis and pre-recorded speech.
• Loquendo text-to-speech gives speech to Activa Multimedia iVAC avatars.