We applied for Google SoC programm 2010 but were rejected. Anyway we appreciate Google's contribution to open souce development. We wish all accepted projects to successfully finish the program this year and we wish good luck to all the students who will participate.

As for us, we still have a lot of tasks that every newbie could put hands on

https://cmusphinx.github.io/wiki/summerofcodeideas

We would be glad to guide anyone who wants to start with them. If you are a student and want to learn more about speech recognition, it's your chance to jump in. We are also open for sponsorship suggestions for this task.

So, CMU Sphinx workshop in Dallas is over. Let us congratulate all participants especially submission authors. That was a great event, the room was full! We were amazed by number of people who attended, their passion and interest in CMU Sphinx. We would be glad to see more participants next year!

For those who missed the workshop, the papers and some slides are available on the website. Certainly you could find something interesting there like new feature release announcements, applications details and new research topics. We didn't forget to support ASR research of course. Workshop was recorded by many recording devices of various types and this data will serve as a database for meeting transcription system.

Of course, the most important side of being on workshop is face-to-face communication. It was important for us to collect and address concerns of our users. Main issues noted were the following:

• Using CMUSphinx in application development. How to make sure the best possible way is taken.
• Using CMUSphinx in research projects. How to get stability guarantees to ensure that work will not be lost or done twice
• Project planning. How to get more information on the project future.

Luckily problems above are mostly organizational issues. There were two development meetings after the workshop to address them. Expect a new announcement about it soon.

We would be glad to continue discussions about CMU Sphinx. Please subscribe to the development mailing list https://lists.sourceforge.net/lists/listinfo/cmusphinx-devel. We would be glad to answer your questions and would appreciate your suggestions.

We are pleased to announce the long-awaited PocketSphinx 0.6 release, including SphinxBase 0.6.  This release corresponds to SVN revision 9898.

PocketSphinx is a small-footprint continuous speech recognition system, freely licensed under a simplified BSD license, suitable for handheld and desktop applications.  It features:

• Cross-platform: Linux, Windows, Mac OS X, iPhoneOS
• Experimental support for Nokia S60v3 and Windows Mobile
• Support for semi-continuous, phonetically-tied, and fully continuous acoustic models
• Model footprint on disk of about 10MB per language
• Memory footprint under 20MB for medium-vocabulary continuous recognition
• Trigram language models and JSGF finite-state grammars
• Acoustic models for English and Mandarin
• Small language models for English and Mandarin (simplified and traditional characters)
• Python language bindings
• GStreamer multimedia framework integration

The release branch can be accessed via Subversion at http://cmusphinx.svn.sourceforge.net/svnroot/cmusphinx/branches/pocketsphinx-0.6 - this is the preferred way to access the release, particularly if you are using Windows.

This exact release tag can be accessed at http://cmusphinx.svn.sourceforge.net/svnroot/cmusphinx/tags/pocketsphinx-0.6

Source code archives are now available for download at http://sourceforge.net/projects/cmusphinx/

Debian/Ubuntu source packages are available from https://launchpad.net/~dhuggins/+archive/cmusphinx

Congratulations with the new release.

Get it here:

https://sourceforge.net/projects/cmusphinx/files/sphinx4/1.0%20beta4/

New Features and Improvements:

• Large arbitrary-order language models
• Simplified and reworked model loading code
• Raw configuration and and demos
• HTK model loader
• Many code optimizations
• JSAPI-independent JSGF parser
• Noise filtering components
• Lattice rescoring
• Server-based language model

Bug fixes:

• Lots of bug fixes: PLP extraction, race-conditions in scoring, etc.

Thanks:

Peter Wolf, Yaniv Kunda, Antoine Raux, Dirk Schnelle-Walka, Yannick Estève, Anthony Rousseau and LIUM team, Christophe Cerisara