This is a small post just to let you know the current state of the TIMIT dataset in Pylearn2. You can find the source code here.

I’m mostly done working on the initialization, thanks to Laurent Dinh’s code.

The dataset is able to load all relevant files, but only the acoustic samples are used. For now I won’t bother including phones/phonemes and auxiliary speaker information, as I have already plenty to manage with the acoustic samples already.

The biggest problem I’m facing is the lack of support for variable-length sequences in Pylearn2. The library is mostly built around the assumption that your data will be a matrix of training examples (with examples being stored in the matrix’s rows) and a matrix of training targets.

One way to circumvent that is to transform the dataset into a matrix of training examples each containing a sequence of k frames and a matrix of training targets each containing the next frame after its corresponding sequence. The problem is it causes lots of duplication in memory.

Another solution would be to keep the dataset as an array of variable-length sequences and maintain a visiting order list of tuples containing the index of a sequence and the index of the starting frame in the sequence. This is where I’m currently headed. One problem with this solution is that no iterator built in Pylearn2 is suited to working with the visiting order list. I’ll have to write one on my own, which might take some time, as I’m not fully fluent with the whole data specs framework used in Pylearn2.

Conclusion: if you’re waiting for me to finish the TIMIT dataset implementation in Pylearn2, this might take some time; you’d be better off working directly in Theano with Laurent’s TIMIT class for now.