Hi All,
This week we will have Navdeep Jaitly, a student with Geoffrey Hinton, who will tell us about his work on Transforming Autoencoders. See you there.
Where: LISA lab (AA3256)
When: 14h00, Thursday, July 28th 2011
Title: Transforming Autoencoders for speech.
Speech
recognition is dominated by use of Gaussian Mixture Model / Hidden
Markov Models trained on mel frequency cepstral representations of
speech. Psychologists have long argued that highy-quality recognition
would be facilitated by finding acoustic events or landmarks that have
well-defined onset times, amplitudes and rates in addition to being
present or absent. We introduce a new way of learning such acoustic
events by using a new type of
autoencoder that is given both a spectrogram and desired global
transformation and learns to output the transformed spectrogram. By
specifying the global transformation in the appropriate way, we can
force the autoencoder to extract accoustic events that, in addition to a
probability of being present, have explicit onset times, amplitudes and
rates. This makes it much easier to compute relationships between
acoustic events.
I'll talk about the work we have done and the directions we are currently pursuing.
This is joint work with Geoffrey Hinton.
Cheers,
Aaron
--
Aaron C. Courville
Département d’Informatique et
de recherche opérationnelle
Université de Montréal
email:Aaron.Courville@gmail.com