An iterative linearised solution to the sinusoidal parameter estimation problem

✍ Scribed by Jean-Marc Valin; Daniel V. Smith; Christopher Montgomery; Timothy B. Terriberry

• Publisher: Elsevier Science
• Year: 2010
• Tongue: English
• Weight: 292 KB
• Volume: 36
• Category: Article
• ISSN: 0045-7906
• DOI: 10.1016/j.compeleceng.2008.11.005

✦ Synopsis

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.