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Resample data based on DTW alignment

Home Page: http://onlinelibrary.wiley.com/doi/10.1002/2015WR017338/abstract;jsessionid=3C7B665AA76118BA2A3756C0DBC09264.f03t03

Python 6.53% Jupyter Notebook 93.47%

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any plans to integrate with LR-DTW?

I think your repos might be just what I need! I am studying neurolinguistics and I would like to use dtw to do two things:

  1. I am simultaneously recording microphone and neural data as people speak repetitions of the same phrase. One common issue is that we speak at slightly different timing every time. I would like to determine the warping from each individual trials to a template using the acoustics, and then apply this warp to the neural data. Could I use this repo for this?

  2. I am also interested in trying to do dtw on the neural data alone, without the acoustics as a base modality, but I am worried that there is too much noise in the neural data for a good warp, and the path I get from naive dtw will be way off. I think I can solve this problem by regularizing the dtw path so that it prefers more direct paths. Could I use LR-DTW for that?

I suppose these use-cases don't necessarily require that your two repos be merged, but I could also see situations where I would want to warp a time series based on a base modality that is noisy and requires regularization.

Very interesting stuff! Thanks for making it public!

Ben

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