ISCA Archive ICSLP 2000
ISCA Archive ICSLP 2000

A cepstrum-based harmonics-to-noise ratio in voice signals

Peter J. Murphy

A new cepstrum-based technique is developed in order to provide an alternative means of estimating the harmonics-to-noise ratio in voice signals. The geometric mean harmonics-to-noise ratio (GHNR) is defined as the mean of the individual spectral (i.e. at specific frequency locations) harmonics-to-noise ratios in dB. A heuristic development of the method treats the harmonic spectrum (in dB) of voiced speech taken over several cycles of the waveform as a more usual time domain signal, which is Fourier transformed. The sum of the resulting cepstral peaks (rahmonics) gives a direct estimation of the geometric mean harmonics-to-noise ratio (GHNR). The need for, inverse Fourier transform of the masked cepstrum back into the frequency domain, baseline correction and the usual harmonics-to-noise ratio (HNR) calculation is avoided by this approach. The technique is examined using synthetically generated voice signals.


Cite as: Murphy, P.J. (2000) A cepstrum-based harmonics-to-noise ratio in voice signals. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 4, 672-675

@inproceedings{murphy00_icslp,
  author={Peter J. Murphy},
  title={{A cepstrum-based harmonics-to-noise ratio in voice signals}},
  year=2000,
  booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
  pages={vol. 4, 672-675}
}