Stephen,

Any thoughts of putting this into Matterhorn as a workflow operation?  I
could imagine getting better performance using a trained acoustic
model, for those instructors who are interested.  Though the audio
sounded nice and clean compared to what we normally get from a mic.

Chris

On Mon, 19 Dec 2011 11:23:55 +0200
Stephen Marquard <[email protected]> wrote:

> Hi all,
> 
> At the Opencast meeting in June in LA, I presented some figures on
> baseline speech recognition performance with Sphinx4 for a set of
> lecture recordings from Open Yale Courses.
> 
> I've now put the complete data set for these online, described at:
> 
> http://trulymadlywordly.blogspot.com/2011/12/sphinx4-speech-recognition-results-for.html
> 
> The figures and resulting output don't look very encouraging, but keep
> in mind that a primary purpose of automated speech recognition is to
> produce searchable time-aligned transcripts rather than a readable
> result.
> 
> I'd be interested in comparative results if anyone runs these
> recordings through another speech recognition engine, or one of the
> hosted services.
> 
> Regards
> Stephen
> 
> 
> Stephen Marquard, Acting Director 
> Centre for Educational Technology, University of Cape Town
> http://www.cet.uct.ac.za
> Email/IM/XMPP: [email protected] 
> Phone: +27-21-650-5037 Cell: +27-83-500-5290 
>  
> 
> 
> 
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