Temporal and spectral estimations of harmonics-to-noise ratio in human voice signals

Abstract

The quantity, harmonic-to-noise ratio (HNR), has been used to estimate the level of noise in human voice signals. HNR estimation can be accomplished in two ways: (1) on a time-domain basis, in which HNR is computed directly from the acoustic waveform; and (2) on a frequency-domain basis, in which HNR is computed from a transformed representation of the waveform. An algorithm for computing HNR in the frequency domain was modified and tested in the work described here. The modifications were designed to reduce the influence of spectral leakage in the computation of harmonic energy, and to remove the necessity of spectral baseline shifting prescribed in one existing algorithm [G. de Krom, J. Speech Hear. Res. 36, 254–266 (1993)]. Frequency-domain estimations of HNR based on this existing algorithm and our modified algorithm were compared to time-domain estimations on synthetic signals and human pathological voice samples. Results indicated a highly significant, linear correlation between frequency- and time-domain estimations of HNR for our modified approach.