An Iterative Linearised Solution to the Sinusoidal Parameter Estimation Problem

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 fr...

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Veröffentlicht in:arXiv.org 2016-02
Hauptverfasser: Valin, Jean-Marc, Smith, Daniel V, Montgomery, Christopher, Terriberry, Timothy B
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:2331-8422
DOI:10.48550/arxiv.1602.05900