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A new adaptive algorithm based upon a least square criterion with a weighting factor is presented and shown to be quite useful for estimating ARMA parameters together with input in speech analysis. The estimator of both the input pulse train for voiced speech and the input white noise for unvoiced speech are easily obtained from the prediction errors by using this new adaptive algorithm. When these estimated inputs are used as the input of the model to be estimated, the influence of the pitch can be eliminated from the estimated ARMA parameters. By using this method the accuracy of formant and antiformant estimators is shown experimentally in comparison with LPC and cepstrum estimators.