![]() ![]() Instead of simple filtering used last time, I wanted to try something more sophisticated in an attempt to achieve improved broad-band noise suppression with minimal audible artefacts. Comparing with the raw clip presented earlier, it is clear that the filters have had an audible effect on suppressing some of the components of the noise. Here is the result of applying the notch filtering to the original noisy clip: Result of applying the notch filtering to the snippet of the raw (noisy) recording in order to suppress the low-frequency noise components. Only three of the notches are being used on the left channel (and only two on the right channel), corresponding to the three noise peaks (at 55 Hz, 1136 Hz, and 1702 Hz) in the left channel (and 55 Hz and 1168 Hz for the right channel). Only the first seven of the left channel filter controls are visible in the screenshot (there are similar controls for each of the ten filters per channel). The plugin has ten notch filters per channel. Figure 3: Screenshot of the MultiNotchFilterStereo plugin (adapted from the MultiNotchFilter plugin bundled with MATLAB) loaded into the MATLAB audioTestBench. Figure 3 shows a (partial) screenshot of the plugin configured to suppress the peaks identified in the spectrum from Figure 2. As a starting point, I used the MultiNotchFilter example “plugin” bundled with the MATLAB Audio Toolbox and extended it to have separate controls for each channel (creating what I call the MultiNotchFilterStereo “plugin”). This allowed me to create a suite of filters which could be separately configured for the left and right channels (since as observed in Figure 2, the characteristics of the noise peaks varies between the channels). However, rather than using Ableton Live’s notch filtering as I did last time, I used MATLAB. Suppressing the “power hum”Īs last time, notch filtering was used to suppress the low-frequency peaks from Figure 2. Also, there is a distinct peak around 1150 Hz in both channels and a lesser peak around 1700 Hz in the left channel only. ![]() Interestingly, the low-frequency power hum (Figure 2) comprises only the fundamental mode (at approximately 60 Hz) rather than the multiple harmonics observed last time. The noise has similar characteristics to the last time: some low-frequency “power hum” (Figure 2) plus a broad-band “tape hiss” over the extent of the audio/music bandwidth (Figure 1). Figure 2: Noise spectrum, zoomed-in on the low-frequency regime, revealing the 60 Hz “power hum” plus a distinct peak around 1150 Hz in both channels and a lesser peak around 1700 Hz in the left channel only. Figure 1: Noise spectrum revealing the broadband nature of the background noise in the recording. Snippet of the raw (noisy) recordingįigures 1 and 2 show the noise spectrum (over the full bandwidth and zoomed-in to the low-frequency zone, respectively) computed via the MATLAB pspectrum function. Here is a clip of the lead-in to the show. In this post, I explain how I cleaned it up using a more elaborate technique than previously.Īgain I used MATLAB for the algorithm development aspects of the process, in combination with Ableton Live for the audio and mix management. Again from an old cassette tape, this recording is rather noisy. I’ve since received another old Havering recording from Walt. Last time I wrote about audio restoration using simple digital filtering (in MATLAB and Ableton Live). ![]()
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