The harmonic-to-noise ratio applied to dog barks.
Dog barks are typically a mixture of regular components and irregular (noisy) components. The regular part of the signal is given by a series of harmonics and is most probably due to regular vibrations of the vocal folds, whereas noise refers to any nonharmonic (irregular) energy in the spectrum of the bark signal. The noise components might be due to chaotic vibrations of the vocal-fold tissue or due to turbulence of the air. The ratio of harmonic to nonharmonic energy in dog barks is quantified by applying the harmonics-to-noise ratio (HNR). Barks of a single dog breed were recorded in the same behavioral context. Two groups of dogs were considered: a group of ten healthy dogs (the normal sample), and a group of ten unhealthy dogs, i.e., dogs treated in a veterinary clinic (the clinic sample). Although the unhealthy dogs had no voice disease, differences in emotion or pain or impacts of surgery might have influenced their barks. The barks of the dogs were recorded for a period of 6 months. The HNR computation is based on the Fourier spectrum of a 50-ms section from the middle of the bark. A 10-point moving average curve of the spectrum on a logarithmic scale is considered as estimator of the noise level in the bark, and the maximum difference of the original spectrum and the moving average is defined as the HNR measure. It is shown that a reasonable ranking of the voices is achievable based on the measurement of the HNR. The HNR-based classification is found to be consistent with perceptual evaluation of the barks. In addition, a multiparametric approach confirms the classification based on the HNR. Hence, it may be concluded that the HNR might be useful as a novel parameter in bioacoustics for quantifying the noise within a signal.