Loudspeaker Equalization for a Moving Listener

Abstract

When a person listens to loudspeakers, the perceived sound is affected not only by the loudspeaker properties but also by the acoustics of the surroundings. Loudspeaker equalization can be used to correct the loudspeaker-room response. However, when the listener moves in front of the loudspeakers, both the loudspeaker response and room effect change. In order for the best correction to be achieved at all times, adaptive equalization is proposed in this paper. A loudspeaker-correction system using the listener's current location to determine the correction parameters is proposed. The position of the listener's head is located using a depthsensing camera, and suitable equalizer settings are then selected based on measurements and interpolation. After correcting for the loudspeaker's response at multiple locations and changing the equalization in real time based on the user's location, a loudspeaker response with reduced coloration is achieved compared to no calibration or conventional calibration methods, with the magnitude-response deviations decreasing from 10.0 to 5.6 dB within the passband of a high-quality loudspeaker. The proposed method can improve the audio monitoring in music studios and other occasions in which a single listener is moving in a restricted space.

Crossover Networks: A Review

“…The magnitude equalization is often implemented using graphic [125][126][127][128] or parametric equalizers [121,129] that are manually or automatically adjusted to approximate a desired target curve. Ramos and Lopez [130] calculate the error areas between the frequency response of the loudspeaker and target curve, and Behrends et al [129] minimize a cost function finding peak filters that best equalize the loudspeaker to the desired target frequency response.…”

A multi-loudspeaker binaural room impulse response dataset with high-resolution translational and rotational head coordinates in a listening room

“…The use of BRIRs has been ubiquitous in many audio applications. For example, in spatial audio reproduction with headphones, BRIRs are used as audio filters to simulate or reproduce an immersive and perceptually plausible sounding environment; in loudspeaker-based applications, the frequency-domain counterparts of BRIRs are equivalent to the acoustic transfer functions between the loudspeakers and the listener's ears, based on which audio filters are designed for tasks such as crosstalk cancellation (Cooper and Bauck, 1989;Gardner, 1998;Choueiri, 2018), room correction/loudspeaker equalization (Karjalainen et al, 1999;Lindfors et al, 2022), and personal sound zones (Druyvesteyn and Garas, 1997;Betlehem et al, 2015;Qiao and Choueiri, 2023a). In addition to audio reproduction and rendering, BRIRs have also played an important role in other audio-related tasks, such as sound source localization (Shinn-Cunningham et al, 2005), sound source separation (Yu et al, 2016), and audio-visual learning (Younes et al, 2023).…”