Okko in Speech

Very quiet recently. No big acquisitions, no no speech-tech revolution.

Most interesting: Google announced Mike Cohen (of formerly Nuance) will appear as keynote speaker at SpeechTek in August to reveal Google’s speech technology strategy. Google has already moved into the speech application market with GOOG411, an automatic directory assistance application leveraging business search and Google Maps.
UBC researchers announce speech learning system that doesn’t use traditional data-driven model to learn the sounds of a language. Instead it is said to represent more experience driven learning, much like infants. So far, the system has acquired English and Japanese vowels.
Some product reviews/announcements: a quick history of desktop dictation, uses of TextAloud for the iPhone, and Nuance’s new South African voice “Tessa”.
Also on the web: NIST evaluates DARPA automatic translation software in military contexts, and What Semantic Search is Not.

I may post less frequently in coming weeks. Stay tuned.

There has been lot’s of German-based language technology news over the past couple of weeks:

• Ulm University in Germany and SpeechCycle parter to develop novel natural language VXML solutions.
• German semgine GmbH secures capital for improved Web3.0 applications, including market-specific, such as biomedical knowledge.
• Berlin-based Lautmaler VUI-design and speech technology experts go online.

Also some attention on language-technology-related search engine news:

• Red Herring roundup of Semantic Technology Conference last month.
• Google adds multilingual search capacity using Google Translate.
• Some speculation on whether video advertisers with enhanced NLP capacities are next in Googles acquisition cross-hairs.

Today, I came across some novel(ish) uses for text-to-speech:

• Security: Campus emergency notification system employs TTS for playback of notifications, sent to student/staff phones.
• Accessibility: ‘Seeingeyephone’ NFC application reads product information to users

On the mainstream speech recognition front:

• Voxeo releases new developer packages, claiming improved internationalization, availability.
• As a reminder of a sadder hour of the industry, Lernout and Houspie goes on trial this week.

And some Web3.0 language tech news:

• This week at the Semantic Technology Conference in San Jose…

On the WWW today:

• Article providing roundup of some semantic web solutions.
• InQuira executive to discuss benefits of NLP for search engine optimization.

Web 3.0 is getting some buzz in the blogosphere. Like Web 2.0, it begs the question that PCMag.com recently ran by its readers: what is it? However this time around things seems a bit easier.

Web 2.0 seems to be happy with being vaguely defined (delimited may be a better term) and equally a social and a technological movement. Web 3.0 clearly hovers over the idea of the “Semantic Web”, a term coined by Tim Berners-Lee, in which richly mark-upped hypertext and data allow for novel more meaningful human-machine and machine-machine communication. Radar Networks (currently in stealth mode) claim to be driving some interesting developments in this direction and are followed closely by those interested.

This has already raised some questions: will content be expensive hand labor or machine boot-strappable, what new privacy policies do we have to live with, how does one separate style and content, what are alternatives to RDF.

Sadly, there’s very little inspiring out there about potential applications.

My question (though not uniquely mine) to add to this: What role will natural language processing play in this (i.e. how “semantic” is this talk of Semantics)? Semantic content in RDF appears to be little more than a means for one machine to tell another who authored a particular book or what are the postal codes in the greater Boston area. Semantics to me is as much about intentions (“Why is web-service A dispensing such information?”) and interpreting such information for the purposes of action (“What can web-service B – or my browser or I – do with it?”).

Perhaps this misses the mark and semantic really isn’t about natural language. But there is a weaker, more real form of this “language and technology” concern: Insofar as semantics is just information, can it be bootstrapped by a machine (perhaps even linguistically informed rather than statistically)?

Thoughts?