so high and gregory usually and form in c and i'll be presenting the work
we did with a bow capture research in preparation for than nist language recognition evaluation
of to some fifteen
so what would it is we just to did for different systems and phonotactic one
us an i-vector system
a long short-term memory recurrent neural network and the lexical couple component
and the main results
that can sure but i will be happy to discuss more a new of the
poster
on that the l s t m r and then can lead to a lower
and lower language error rate than i-vectors
still the phonotactic system is the most robust with a method especially when you data
are available for language
and when facing are very strong mismatch between training and testing which was the case
for the lre or fifteen
and a what's worse really interesting for ice is that the phonotactic system and the
l s t n r and then really combined their combine really well in that
the combination of the two system lead to an important a language or rate reduction
and if you want to know more about the few euros here
i you have to come and see the poster in speaker and me thank you