The LISTEN set from IRCAM, the KEMAR set from MIT and the spherical set
by R. Duda are included in the Ambisonic Toolkit. I use them on
http://ambisonic.xyz/ . The spherical set is probably a good enough
compromise for VR applications, because perfection is not required for a
good experience. What seems to be missing is a practical method to
provide personalized HRTFs to users.
--
Marc

On Sun, 24 Jan 2016 19:31:33 +0000,
Stefan Schreiber <[email protected]> wrote :

> http://www.blueripplesound.com/hrtf-amber
> 
> > The IRCAM AKG "Listen" HRTF data contains measured HRTFs from about
> > 50 different people - this must have taken a lot of effort and
> > we're very grateful to the good folk of IRCAM for doing the work
> > and making the results available to the world! What we've done is
> > analyse this data and come up with an 'average' HRTF that is a
> > sensible compromise, using some new work. As it's an average, it
> > wouldn't be perfect for any of the people actually measured, but
> > hopefully not awful for any of them either! It's certainly much
> > better than conventional "panning" techniques.
> 
> 
> (See also:
> 
> http://www.blueripplesound.com/personalized-hrtfs
> )
> 
> > We provide "generic" HRTFs models (for instance, our Amber HRTF 
> > <http://www.blueripplesound.com/hrtf-amber>) which work well for
> > many people, but even better results can be achieved using
> > personalized HRTF measurements.
> 
> 
> Could any people, companies or institutions on this list provide
> access to such a practical and < usable > generic HRTF model?
> 
> If not: I believe that some essential theses and papers should have
> been done in the academic world, but don't exist anyway.
> 
> Richard Furse basically states that a "good" generic HRTF is derived 
> from many HRTF measurements (data sets) via some  form of averaging,
> as a "sensible compromise". I doubt that this is a trivial process,
> though...
> 
> Best regards,
> 
> Stefan
> 
> 
> P.S.:  VR companies will currently have to look into these issues,
> and to find solutions which are practical at least < for most >
> people. If some proposed HRTF data set doesn't fit to an individual
> listener it should be pretty hard to distinguish between front/back
> sources, for example. (Even with head-tracking.)
> 
> Don't tell me that I didn't present a paper to prove my point... 
> Instead, give me the link to a paper which delivers some kind of 
> optimized generic HRTF data set. If such a paper doesn't exist (yet),
> I don't see any reason why something like "Amber HRTF" can't be 
> re-engineered.
> (Amber HRTF itself is derived from IRCAM AKG "Listen" HRTF data, a 
> public available list. And even IRCAM should be interested to provide
> a good universal  HRTF based on its own and public HRTF research!)
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