Michael J. Terrell

Automatic noise gate settings for drum recordings containing bleed from secondary sources

An algorithm is presented which automatically sets the attack, release, threshold, and hold parameters of a noise gate applied to drum recordings which contain bleed from secondary sources. The gain parameter which controls the amount of attenuation applied when the gate is closed is retained, to allow the user to control the strength of the gate. The gate settings are found by minimising the artifacts introduced to the desirable component of the signal, whilst ensuring that the level of bleed is reduced by a certain amount. The algorithm is tested on kick drum recordings which contain bleed from hi-hats, snare drum, cymbals, and tom toms.

An offline, automatic mixing method for live music, incorporating multiple sources, loudspeakers, and room effects

A model of live performance is presented that includes simplified acoustic-environmental system models and enables the coupling behavior between multiple sources and receivers to be predicted. The model allows the mix at each location within the performance space to be evaluated as a function of the acoustic signals generated by the instruments and of the control parameters on the mixing desk, through which the instrument signals are sent before being reinforced using loudspeakers. For a set of listener locations, which includes both performers and members of the audience, ideal mixes are defined, and an optimization algorithm is developed that sets the control parameters on the mixing desk automatically, to deliver approximations of these ideal mixes to all listener locations simultaneously. The control parameters are constrained during the optimization to prevent the onset of acoustic feedback. The algorithm is examined, and we show that a targeted approach, which first sets the control parameters relating the vocal level, gives a better solution in a shorter time when compared to a brute-force approach.

Rearrangement of Timbre Space Due To Background Noise: Behavioural Evidence and Acoustic Correlates

Asterios Zacharakis1), Michael J. Terrell2), Andrew J. R. Simpson3), Konstantinos Pastiadis1), Joshua D. Reiss4) 1) Aristotle University of Thessaloniki, School of Music Studies, Thessaloniki, Greece. aszachar@mus.auth.gr 2) Independent Researcher 3) University of Surrey, Centre for Vision, Speech and Signal Processing, Surrey, GU2 7XH, UK. 4) Queen Mary University of London, Centre for Digital Music, Mile End Road, London, E1 4NS, UK.