Abstract
The effect of using different auditory images and distance metrics on the final configuration of a self-organized timbre map is examined by comparing distance matrices obtained from simulations with a similarity rating matrix, obtained using the same set of stimuli as in the simulations. Two approaches are described. In the static approach, each stimulus is represented as a single multi-component vector. Gradient images, which are intended to represent idealizations of physiological gradient maps in the auditory pathway, are constructed. The optimal auditory image and distance metric, with respect to the similarity rating data, are searched using the gradient method. In the dynamic approach, each input stimulus is represented by a set of spectral vectors.The response patterns are constructed through temporal integration. The onset portions of the stimuli are emphasized using a scaling procedure which operates qualitatively in the same way as lateral inhibition.
Preview
Unable to display preview. Download preview PDF.
References
Cosi, P., De Poli, G., & Lauzzana, G. (1994). Auditory modelling and selforganizing neural networks for timbre classification. Journal of New Music Research, 23, 71–98.
De Poli, G., Prandoni, P., & Tonella, P. (1993). Timbre clustering by selforganizing neural networks. In G. Haus & I. Pighi (Eds.), Proceedings of the Xth Colloquio di Informatica Musicale. Milan: AIMI.
Feiten, B., & Günzel, S. (1994). Automatic indexing of a sound database using self-organizing neural nets. Computer Music Journal, 18, 53–65.
Iverson, P., & Krumhansl, C. (1993). Isolating the dynamic attributes of musical timbre. The Journal of the Acoustical Society of America, 94, 2595–2603.
Kohonen, T. (1995). Self-organizing maps. Berlin, Heidelberg: Springer-Verlag.
Leman, M. (1994). Schema-based tone center recognition of musical signals. Journal of New Music Research, 23, 169–204.
Pickles, J. (1982). An introduction to the physiology of hearing. London: Academic Press.
Ru, P., & Shamma, S. (1997). Representation of musical timbre in the auditory cortex. Journal of New Music Research, 26.
Shamma, S., Vranic, S., & Wiser, P. (1992). Spectral gradient columns in primary auditory cortex: Physiological and psychoacoustical correlates. Advances in the Biosciences, 83, 397–404.
Steiger, H., & Bregman, A. (1981). Capturing frequency components of glided tones: Frequency separation, orientation, and alignment. Perception and Psychophysics, 30, 425–435.
Toiviainen, P. (1996). Optimizing auditory images and distance metrics for self-organizing timbre maps. Journal of New Music Research, 25, 1–30.
Toiviainen, P., Kaipainen, M., & Louhivuori, J. (1995). Musical timbre: Similarity ratings correlate with computational feature space distances. Journal of New Music Research, 24, 282–298.
Van Immerseel, L., & Martens, J. (1992). Pitch and voiced/unvoiced determination with an auditory model. The Journal of the Acoustical Society of America, 91, 3511–3526.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Toiviainen, P. (1997). Optimizing self-organizing timbre maps: Two approaches. In: Leman, M. (eds) Music, Gestalt, and Computing. JIC 1996. Lecture Notes in Computer Science, vol 1317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0034124
Download citation
DOI: https://doi.org/10.1007/BFb0034124
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63526-0
Online ISBN: 978-3-540-69591-2
eBook Packages: Springer Book Archive