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Extra resources for Advances in Sound Localization
4) However, since the length of the acoustic transfer function is greater than that of the window, the observed spectrum is approximately represented by O(ω; n) ≈ S(ω; n) · H (ω; n). Here O(ω; n), S(ω; n), and H (ω; n) are the short-term linear complex spectra in analysis window n. Applying the logarithm transform to the power spectrum, we get log |O(ω; n)|2 ≈ log |S(ω; n)|2 + log | H (ω; n)|2 . (5) In speech recognition, cepstral parameters are an effective representation when it comes to retaining useful speech information.
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Concerning the null contours of vector sensors, Proc. Meetings on Acoustics, Vol. 9, Acoustical Society of America. Schmidlin, D. J. (2010c). The directivity index of discriminating functions, Technical Report No. 31-2010-1, El Roi Analytical Services, Valdese, North Carolina. Schmidt, R. O. (1986). Multiple emitter location and signal parameter estimation, IEEE Trans. Antennas and Propagation, Vol. AP-34, No. 3, pp. 276-280. Silvia, M. T. (2001). A theoretical and experimental investigation of acoustic dyadic sensors, SITTEL Technical Report No.
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