Pascal1K
Flickr8K (ImagesData)
TODO: one line on the code to transform LUCID into our dataset.
TODO: one line on the code to extract R-CNN features from images.
To train the multi-modal embedding net, do:
THEANO_FLAGS="device=gpu1" python run_exp_AB.py --dataset-path=/fhgfs/bootphon/scratch/gsynnaeve/learning_semantics2014/pascal_full/ --prefix-output-fname="maxnorm" --debug-print=1 --debug-time
TODO: scores && plots
(On Mac OS X only)
Use bash say_words.sh
with a words.txt file in the same directory. Then you
can sox
the produced *.aif
to *.wav
files (you may need to for
loop),
then transform them to filterbanks with python mfsc.py *.wav
(for
too) and
finally put them in one big *.npz
formatted dictionary with
python npz_fbanks.py FOLDER
.
Finally use python simple_dnn.py
to train a DNN if wanted (look into it).