University of London silences the vuvuzela

University of London silences the vuvuzela
Queen Mary, University of London has come to the rescue of disgruntled football fans that don’t appreciate the trumpeting of vuvuzelas. Its Centre for Digital Music (C4DM) has developed a “devuvuzelator” that, it claims, doesn’t impede the clarity of the match commentary.

This world cup has been marked by the raucous sound of vuvuzelas across South Africa’s stadiums. Whilst the celebratory trumpeting is welcomed by some it has sparked numerous complaints to broadcasters from fans that complain the instrument drowns out the commentary and replaces atmospheric chanting and celebration with a continuous drone.

Thanks to researchers at C4DM anyone watching the World Cup on their computer can now filter out the sound of vuvuzelas.

Dr Chris Cannam and a team of researchers from the C4DM have analysed the sound and devised a filter, which could improve the clarity of the commentary. The filter is downloadable as a working "devuvuzelator" and is claimed to largely remove the sound of the instruments.

Various approaches have been discussed by audio engineers, most commonly using "notch filtering", which removes sound energy from specific frequencies. The vuvuzela sound energy is mostly found within narrow frequency bands - the fundamental frequency (approximately 230 Hz) and some higher overtones - so targeting those specific frequencies is a reasonable way to quieten the vuvuzela sound. Unfortunately, notch filtering also has a tendency to remove some of the energy from the commentator's voice too, since the frequency distributions of the voice and vuvuzela overlap.

Dan Stowell of the C4DM said, "Our approach was to make a filter which estimates the amount of energy in the signal contributed by vuvuzelas, at the specific frequencies expected, and then subtracts just that energy. This 'adaptive' approach potentially preserves the voice energy in the signal and helps preserve voice quality."

The C4DM's filter adds a degree of intelligence beyond ordinary filters. It is actually not as complex as some of the techniques developed by the group, such as source-separation algorithms which can take a recording containing a singer and a piano and work out how to extract just the singer's voice. But the filter is simple enough that it can be run in real-time and applied to a live broadcast as it happens, on an ordinary home computer.

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