Date of Award


Degree Name

MS in Electrical Engineering


Wayne Pilkington



Improving broadband noise filter for audio signals


Alex Conway

Filtering broadband noise in audio signals has always been a challenge since the noise is spread across a large bandwidth and overlaps the spectral range of the audio signal being recovered. There have been several broadband noise reduction techniques, such as spectral subtraction, developed for speech enhancement that might be applied to reduce noise in musical audio recordings as well. One such technique that is investigated in this thesis identifies the harmonic components of a signal to be preserved as those spectral magnitude peaks that exceed a chosen decision threshold. All other spectral components below the threshold are considered to be noise. Noise components are then attenuated enough to render them imperceptible in the presence of the harmonic signal, using a psycho-acoustical model of sound masking.

The objective of this thesis is to show that this algorithm can be adapted and improved for musical audio noise reduction. Improvements include relaxing the filter when percussion events are anticipated, since these appear spectrally similar to broadband noise but are essential to the musical experience; and using harmonic prediction to preserve more of the signal harmonics than the simple threshold would pass. Harmonic prediction takes advantage of the known harmonic spacing of musical content and places noise filter pass bands around a fixed number of harmonics of every fundamental pitch found; passing some harmonics that would get filtered out by the original thresholding algorithm.

Noise filtering improvements were assessed for both noise reduction and signal degradation effects by different signal to noise ratio computations. The audio results with and without improvements were also assessed using subjective listening tests, since how the sound is perceived is what matters most in musical recordings. Quantitative results show improved signal to noise ratios of filtered audio signals when the improvements were included compared to the original threshold-based filter. Perceived sound quality in listening tests was also higher with the percussion preservation and harmonic prediction improvements. In all listening tests, every listener rated the improved filter as the best.