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IFT6266 Project on Representation Learning | A great WordPress.com site
IFT6266 Project on Representation Learning. A great WordPress.com site. Results with ReLUs and different subjects. May 1, 2014. I ran some more experiments based on my previous post:. Using ReLUs on the hidden layers. Using more hidden units in the NSNN. Training/generating with other speakers. 1 Using ReLUs on the hidden layers. NSNN: 2 hidden layers (200 and 150 units). WNN: 1 hidden layer (250 units). Number of epochs: 500. This effect was found to disappear after around 75 epochs. The training proced...
ift6266sina.wordpress.com
Sina Honari's blog for Representation Learning | My blog on the Representation Learning Course
Sina Honari's blog for Representation Learning. My blog on the Representation Learning Course. Skip to primary content. Skip to secondary content. Fine tuning of unsupervised pretraining. May 11, 2013. Here are the results for the model with GCN preprocessing. In both experiments I had to set the learning rate to 1e-5. The training algorithm diverged using higher values of the learning rates . As the results demonstrate, sigmoid units work better with GCN. May 10, 2013. In the next attempt, I used unsupe...
ift6266speechsynthesisjt.wordpress.com
Experiments in deep learning for speech synthesis | Jessica Thompson's journal for IFT6266 – Representation Learning at Université de Montréal
Experiments in deep learning for speech synthesis. Jessica Thompson's journal for IFT6266 – Representation Learning at Université de Montréal. Skip to primary content. Skip to secondary content. January 24, 2014. This blog will document my progress on the final project for Dr. Yoshua Bengio’s course on Representation Learning. The task for the project is speech synthesis. April 30, 2014. Vincent published a blog post on h ow to use the Pylearn2 TIMIT class with multiple sources, specifically c. Monitor i...
ift6266tr.wordpress.com
Speech synthesis experiments | Smile! You’re at the best WordPress.com site ever
You’re at the best WordPress.com site ever. The plan, at this point, is to use a gammatone dictionary and sparse coding to train more efficiently on the TIMIT dataset. Gammatone functions are filters applied on frequencies. The goal is to keep frequencies processed by our ears. Joao explains this greatly in his blog. The idea is to use this sparse-coded version as input of a spike and slab RBM segmented by frames of 160 samples and with the previous, current and next phones. I kept the parameters use...
ift6266vaudrypl.wordpress.com
IFT6266 project | Experiments in speech synthesis with neural networks by Pierre-Luc Vaudry
Experiments in speech synthesis with neural networks by Pierre-Luc Vaudry. Predicting the standard deviation. Hubert Banville successfully implemented the kind of architecture I also had in mind. In this experiment, I wanted to see if having this standard deviation predicted by the neural network could improve the results. I based myself on Hubert’s code, which is described in his last post. To this loss function, the L1 and L2 norm penalties are also added as regulators, as in Hubert’s experiments...
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New in this week. Http:/ www.ift891.org/modules/mod image show gk4/cache/demo.is demogk-is-228.png. Jamie Cullum the …. 十一月 07, 2011. Http:/ www.ift891.org/modules/mod image show gk4/cache/demo.is demogk-is-228.png. Both JLS and Will…. 十一月 07, 2011. Http:/ www.ift891.org/modules/mod image show gk4/cache/demo.is demogk-is-228.png. U2 Tower land to …. 九月 09, 2011. Http:/ www.ift891.org/modules/mod image show gk4/cache/demo.is demogk-is-228.png. New boyband & hellip;. 九月 08, 2011. David Nail in the…. Http:/...
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