Resources

Notes

Hopefully someone else might also find these notes useful. Let me know if you find any mistakes or have any comments.

  • Yet another introduction to backpropagation. [pdf]
  • Gibbs sampling for fitting finite and infinite Gaussian mixture models. [pdf, code]
  • Vector and matrix calculus. [pdf]

Invited talks

  • Learning from unlabelled speech, with and without visual cues. Ohio State University, 2017. [slides]
  • Learning from unlabelled speech, with and without visual cues. University of Maryland, CLIP Colloquium Speaker, 2017.
  • Unsupervised neural and Bayesian models for zero-resource speech processing. MIT, Computer Science and Artificial Intelligence Laboratory, 2016. [slides]
  • Unsupervised speech processing using acoustic word embeddings. Workshop on Machine Learning in Speech and Language Processing, Spotlight Speaker, 2016. [slides]

Code

Most of my code is available on GitHub, as also noted with each of the publications. Below is a summary of some of the main repositories.