Performance and optimization of the SEEVOC algorithm

In most low bit rate coders, the quality of the synthetic speech depends greatly on the performance of the spectral coding stage, in which the spectral envelope is estimated and encoded. The Spectral Envelope Estimation Vocoder (SEEVOC) is a successful spectral envelope estimation method that plays an important role in low bit rate speech coding based on the sinusoidal model. This paper investigates the properties and limitations of the SEEVOC algorithm, and shows that it can be generalized and optimized by changing the search range parameters α and β. Rules for the optimum choice of α and β are derived, based on both analysis and experimental results. The effects of noise on the SEEVOC algorithm are also investigated. Experimental results show that the SEEVOC algorithm performs better for voiced speech in the presence of noise than linear prediction (LP) analysis.