Difference between revisions of "VS298 (Fall 06): Suggested projects"

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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.)
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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.)
  
* Recognition of handwritten digits.   
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* '''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