An iterative linearised solution to the sinusoidal parameter estimation problem |
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Authors: | Jean-Marc Valin [Author Vitae] Daniel V. Smith [Author Vitae] Timothy B. Terriberry [Author Vitae] |
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Affiliation: | a CSIRO ICT Centre, Cnr. Vimiera and Pembroke Roads, Marsfield NSW 2122, Australia b Tasmanian ICT Centre, CSIRO, Castray Esplanade, Hobart Tasmania, 7004, Australia c RedHat Inc., 314 Littleton Road, Westford, MA 01886, USA d Xiph.Org Foundation, 21 College Hill Road, Somerville, MA 02144, USA |
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Abstract: | Signal processing applications use sinusoidal modelling for speech synthesis, speech coding, and audio coding. Estimation of the model parameters involves non-linear optimisation methods, which can be very costly for real-time applications. We propose a low-complexity iterative method that starts from initial frequency estimates and converges rapidly. We show that for N sinusoids in a frame of length L, the proposed method has a complexity of O(LN), which is significantly less than the matching pursuits method. Furthermore, the proposed method is shown to be more accurate than the matching pursuits and time-frequency reassignment methods in our experiments. |
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Keywords: | Sinusoidal modelling Iterative least-squares solution |
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