Experimental Data-Driven Estimation of Impulse Response in Audio Systems Using Parametric and Non-Parametric Methods

The impulse response is a fundamental tool for characterizing linear time-invariant (LTI) systems, enabling the derivation of a mathematical model that accurately describes system dynamics under arbitrary input conditions. This study used experimental data to estimate the impulse response of an audio system—comprising an amplifier, a speaker, a room, and a microphone. Four methods were employed: two parametric and two non-parametric approaches, applied in both the time and frequency domains. The methods were evaluated quantitatively using the Root Mean Square Error (RMSE) metric and qualitatively through a perceptual analysis with six participants. The parametric frequency-domain method achieved the best perceptual results, with 75% of participants rating the output as good. While this method exhibited slightly higher RMSE compared to other techniques, its low filter order (8) resulted in superior computational efficiency. The findings highlight that perceptual alignment often diverges from purely mathematical error minimization. Real-time implementation of the selected impulse response further demonstrated its practical application in audio processing systems. This research bridges quantitative metrics and human auditory perception, emphasizing the need for balanced decision-making in audio system modeling. The results contribute to advancing data-driven methodologies in acoustics, offering insights into both experimental design and computational efficiency