Robust and efficient pitch estimation using an iterative ARMA technique

In this article, we propose an innovative way of estimating pitch from speech waveform data, using an iterative ARMA technique that efficiently estimates multiple frequency components of a time series. Additionally, the harmonic structure of voiced speech and the smoothness of its pitch period are incorporated into the iterative ARMA technique, and this novel integration results in an efficient, robust technique for pitch estimation. The KED-TIMIT database was used to evaluate the performance of our proposed algorithm against that of other state-of-the-art pitch estimators in terms of both root mean square error and gross error rate.