Ph. D. Dissertation

  • Sparse Approximation and Atomic Decomposition: Considering Atom Interactions in Evaluating and Building Signal Representations (2009) (PDF) (slides)

Journal Articles

  1. M. Morvidone, B. L. Sturm and L. Daudet, “Scale-dependent Mel-frequency Cepstral Coefficients Based on Sparse Representations and Musical Instrument Recogntion,” Patt. Recogn. Lett. (submitted).
  2. B. L. Sturm and J. J. Shynk, “Sparse approximation and the pursuit of meaningful signal models,” IEEE Trans. Acoustics, Speech, Signal Process. (submitted).
  3. B. L. Sturm, C. Roads, A. McLeran, and J. J. Shynk, “Analysis, Visualization, and Transformation of Audio Signals Using Dictionary-based Methods,” Journal of New Music Research, 2009. (invited.)
  4. B. L. Sturm, J. J. Shynk, L. Daudet, and C. Roads, “Dark energy in sparse atomic estimations,” IEEE Trans. Audio, Speech, Lang. Process., vol. 16, no. 3, pp. 671-676, 2008.

Tutorial Slides

  1. B. L. Sturm, "Dictionary-based Methods (Sparse Approximation) for Audio Signals," Sound and Music Computing Conference, (Porto, Portugal), July, 2009. (slides, 95MB)

Conference Papers

  1. B. L. Sturm and L. Daudet, “Similarity Search in Audio Signals Using Sparse Approximations,” Int. Symp. Music Info. Retrieval (submitted).
  2. B. L. Sturm, J. J. Shynk, and D. H. Kim, “Pruning Sparse Signal Models Using Interference,” in Proc. Conf. Info. Sciences Syst., (Baltimore, MD), Mar. 2009.
  3. B. L. Sturm and J. J. Shynk, “Interference-driven adaptation in sparse approximations,” in Proc. Asilomar Conf. Signals, Syst., Comput., (Pacific Grove, CA), Oct. 2008.
  4. B. L. Sturm, C. Roads, A. McLeran, and J. J. Shynk, “Analysis, Visualization, and Transformation of Audio Signals Using Dictionary-based Methods,” Proc. Int. Conf. Computer Music, Belfast, Ireland, August 2008. (Voted best paper of conference.) (Sound examples here.)
  5. B. L. Sturm, J. J. Shynk, C. Roads, A. McLeran, and L. Daudet, “A comparison of molecular approaches for generating sparse and structured multiresolution represen-tations of audio and music signals,” Proc. Acoustics, Paris, France, June 2008.
  6. B. L. Sturm, J. J. Shynk, and L. Daudet, “Measuring Interference in Sparse Atomic Estimations,” Proc. Conf. Info. Sciences Syst., Princeton, NJ, March 2008.
  7. B. L. Sturm, J. J. Shynk, and S. Gauglitz, “Agglomerative clustering in sparse atomic decompositions of audio signals,” Proc. IEEE Int. Conf. Acoustics, Speech, Signal Process., Las Vegas, NV, Mar. 2008.
  8. B. L. Sturm, J. J. Shynk, and L. Daudet, “A Short-term Measure of Dark Energy in Sparse Atomic Estimations,” Proc. Asilomar Conf. Signals, Syst., Comput., Asilomar, CA, Nov. 2007.
  9. B. L. Sturm, L. Daudet, and C. Roads, “Pitch-shifting Audio Signals Using Sparse Atomic Approximations,” Proc. ACM Workshop Audio Music Comput. Multimedia, pp. 45–52, Santa Barbara, CA, Oct. 2006. (Sound examples here.)
  10. B. L. Sturm and J. D. Gibson, “Matching Pursuit Decompositions of Non-noisy Speech Signals Using Several Dictionaries,” Proc. IEEE Int. Conf. Acoustics, Speech, Signal Process., Toulouse, France, Apr. 2006.

Research: Sparse Approximation

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The motivations for exploring sparse approximation in digital systems and signals include the desire to express complex data in sparse, efficient, and meaningful ways than can be provided by orthogonal and linear transforms. Since acoustical data has multiple structures that cannot be efficiently represented using a single basis, e.g., the Fourier basis, sparse approximation methods promise to deliver sparse and structurally meaningful representations of such data for use in applications of analysis (e.g., source discrimination), visualization (e.g., source selection), and transformation (e.g., source separation). I am investigating ways of applying sparse approximation to building and enhancing the interface between a user and the content of acoustical data. I am also interested in optimizing methods for sparse approximation on high-dimensional datasets. To the left is a list of my various papers on these subjects, with links where possible.