Estimation du spectre du signal de parole en présence d'un bruit de fond coloré

Abstract

A modified SEARMA method is proposed for estimating the speech spectrum in the presence of colored background noise. The following assumptions are used in developing the analysis . The speech production process is represented by an autoregressive moving-average (ARMA) mode] . The background noise is represented by an MA process . The noise process is locally stationary during speech activity. Following these assumptions, the process during speech activity can be represented by an extended ARMA model . In this formulation, unique estimation of AR parameters of the vocal tract transfer function is always possible if the MA parameters of the noise process can be estimated separately, but the estimation of MA parameters of the speech production process requires further assumption of a high SNR . The validity of the proposed method is demonstrated by spectral estimation of both synthetic and natural speech sounds in the presence of additive colored noise, and by comparing the results with those obtained by the LPC method .Le signal de parole est représenté par un modèle autorégressif à moyenne mobile étend