Title :
An improved (Auto:I, LSP:T) constrained iterative speech enhancement for colored noise environments
Author :
Pellom, Bryan L. ; Hansen, John H L
Author_Institution :
Dept. of Electr. Eng., Duke Univ., Durham, NC, USA
fDate :
11/1/1998 12:00:00 AM
Abstract :
We illustrate how the (Auto:I, LSP:T) constrained iterative speech enhancement algorithm can be extended to provide improved performance in colored noise environments. The modified algorithm, referred to as noise adaptive (Auto:I, LSP:T), operates on subband signal components in which the terminating iteration is adjusted based on the a posteriori estimate of the signal-to-noise ratio (SNR) in each signal subband. The enhanced speech is formulated as a combined estimate from individual signal subband estimators. The algorithm is shown to improve objective speech quality in additive noise environments over the traditional constrained iterative (Auto:I, LSP:T) enhancement formulation
Keywords :
acoustic noise; iterative methods; maximum likelihood estimation; speech enhancement; (Auto:I, LSP:T) constrained iterative speech enhancement; a posteriori estimate; additive noise environments; colored noise environments; constrained iterative Auto-LSP speech enhancement algorithm; enhanced speech; noise adaptive (Auto:I, LSP:T); objective speech quality; performance; signal subband estimators; signal-to-noise ratio; subband signal components; subbanded signal components; terminating iteration; Acoustic noise; Background noise; Colored noise; Degradation; Iterative algorithms; Iterative methods; Signal to noise ratio; Speech enhancement; Speech processing; Working environment noise;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on