|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
THE STATE SPACE AND "IDEAL INPUT" REPRESENTATIONS OF RECURRENT NETWORKS
This paper looks at the data representations used in recurrent networks for two of the supplied sentences for the workshop. One sentence from the database on which the network was trained (timit) is used to illustrate the input, state and output representations for clean speech. Another sentence (clean) is used to illustrate the degradation that results from different recording conditions. Gradient descent in the input space is used on the second sentence so as to make the output better conform to the assumed pronunciation.
If you have difficulty viewing files that end
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
If you have difficulty viewing files that are in PostScript, (ending
'.ps.gz'), then you may be able to
find tools to view them at
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.
|| Search | CUED | Cambridge University ||
2005 Cambridge University Engineering Dept
Information provided by milab-maintainer