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Thirty Tips For Dissertation Writing

Earlier today, I attended an excellent workshop by Dr. Rachna Jain on writing the dissertation. About 150-200 students attended. Here is some of her advice. Continue Reading…

Engineers Build Computerized Beauty Contest Judges. Swell.

I was browsing Stack Overflow when I came across this question that asks how to use image processing and machine learning to measure the beauty of a human face. As this answer explains, papers have already been written on the topic, including this one in ECCV 2010. Continue Reading…

Resumé Template in LaTeX

People have been asking for the LaTeX template that I used to build my resumé/CV. Here it is: Continue Reading…

The One-Step Build for Academic Researchers

The Joel Test is a set of twelve simple yes/no questions written by Joel Spolsky that is supposed to measure how good a software team is. Some of these questions include “Do you have a spec?”, “Do you have testers?”, and “Do you use source control?”. A software team that can answer “yes” to all twelve questions probably produces excellent software, according to Spolsky. Continue Reading…

I used Matlab. Now I use Python.

Colleagues have asked me why I changed from Matlab to Python, and what makes Python so great. For example, a friend recently asked the following: Continue Reading…

Summary: Musical Instrument Recognition Using Biologically Inspired Filtering of Temporal Dictionary Atoms

Musical Instrument Recognition Using Biologically Inspired Filtering of Temporal Dictionary Atoms

  • Steven K. Tjoa and K. J. Ray Liu
  • Int. Soc. Music Information Retrieval Conf., August 2010
  • Download: Paper, Poster, BibTeX
    @INPROCEEDINGS{tjoa2010ismir,
      title = "Musical Instrument Recognition Using Biologically Inspired Filtering of Temporal Dictionary Atoms",
      author = "Steven K. Tjoa and K. J. Ray Liu",
      booktitle = "Proc. Int. Soc. Music Information Retrieval Conf.",
      address = "Utrecht, Netherlands",
      year = "2010",
      month = aug,
      pages = "435--440"
    };

Most musical instrument recognition systems rely upon spectral information to classify sounds. Can temporal information improve classification accuracy even further? Continue Reading…

Summary: Multiplicative Update Rules for Nonnegative Matrix Factorization with Co-occurrence Constraints

Multiplicative Update Rules for Nonnegative Matrix Factorization with Co-occurrence Constraints

  • Steven K. Tjoa and K. J. Ray Liu
  • IEEE Int. Conf. Acoustics, Speech, and Signal Processing, March 2010
  • Download: Paper, Poster, BibTeX
    @INPROCEEDINGS{tjoa2010icassp_cooccurrence,
      title = "Multiplicative Update Rules for Nonnegative Matrix Factorization with Co-occurrence Constraints",
      author = "Steven K. Tjoa and K. J. Ray Liu",
      booktitle = "Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing",
      address = "Dallas, TX",
      year = "2010",
      month = mar,
      pages = "449--452"
    };

Nonnegative matrix factorization (NMF) has become a popular tool for discovering structure in a variety of signals. When applied to a musical audio signal, NMF builds a set of dictionary atoms that represent the individual musical sources in the signal. To perform music transcription, we map the learned dictionary atoms to musical notes and beats. Continue Reading…