9 Mar
2009
9 Mar
'09
8:59 a.m.
alex stone wrote:
If you're intent on automating a speech analysis,
voice noise removal
device of some sort, then you might do well to start with a 'pre and
post' framework. Things like lipsmacking, glottal and nasal noise for
the end of phrase, etc, are fairly easy to identify, and generally occur
pre and post. So that may well be a decent percentage of any cleanup
done quickly. (Dependent of course on language. Cleaning up russian
would be a different 'module' to cleaning up French, or Finnish.)
That sounds encouraging. What to you mean by "pre and post" (sorry if that's
an
obvious question to you)?
And maybe there's a coding clue there too. A
modular, language centric
approach, based on loading a module designed specifically for a
particular language and phrasal interpretation. (Module 1 spoken=French,
Module 2 sung=French, Module 3 spoken=Finnish, etc....)
I think you're right. There's nothing universal about making noise and actually
meaning something ;)
--
Olivier