VS298 (Fall 06): Suggested projects: Difference between revisions
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* NETtalk. Train a multi-layer perceptron to convert text to speech. You can get Sejnowski & Rosenberg's original paper and the data they used [http://www.cnl.salk.edu/ParallelNetsPronounce/index.php here]. (You will need a DECtalk speech synthesizer to play the phonemes - you can probably pick up a used one online.) | * '''NETtalk.''' Train a multi-layer perceptron to convert text to speech. You can get Sejnowski & Rosenberg's original paper and the data they used [http://www.cnl.salk.edu/ParallelNetsPronounce/index.php here]. (You will need a DECtalk speech synthesizer to play the phonemes - you can probably pick up a used one online.) | ||
* Recognition of handwritten digits. | * '''Recognition of handwritten digits.''' Train a MLP to classify handwritten digits 0-9. You can get some training data [http://yann.lecun.com/exdb/mnist/ here]. You may wish to follow the convolutional network methodology of [http://yann.lecun.com/exdb/lenet/index.html Yann LeCun] (try the simpler, [http://yann.lecun.com/exdb/publis/pdf/lecun-89e.pdf earlier model]), or invent your own method. | ||
* Foldiak network | * Foldiak network | ||
Revision as of 01:42, 23 October 2006
- NETtalk. Train a multi-layer perceptron to convert text to speech. You can get Sejnowski & Rosenberg's original paper and the data they used here. (You will need a DECtalk speech synthesizer to play the phonemes - you can probably pick up a used one online.)
- Recognition of handwritten digits. Train a MLP to classify handwritten digits 0-9. You can get some training data here. You may wish to follow the convolutional network methodology of Yann LeCun (try the simpler, earlier model), or invent your own method.
- Foldiak network
- Cortical maps
- Feedforward vs. Recurrent weights in networks
- Restricted Boltzmann machines
- Integrate-and-fire model neuron
