Towards reproducible evaluation of automotive hands-free systems in dynamic conditions

Reproducible evaluation of dynamic and nonlinear systems is a nontrivial problem. However, automotive speech processing algorithms such as hands-free systems have to be tested under numerous time-variant conditions in a repeatable fashion. The current way of generating time-varying echo paths, as described in ITU-T Recommendation P.1110, relies on a rotating reflecting surface in a car interior, which lacks both flexibility and reproducibility. We propose an automotive loudspeaker-enclosure-microphone (LEM) system-identification approach based on the normalized least mean squares (NLMS) algorithm and a perfect sweep excitation signal. Time-variant simulations of a nonlinear system model show a significant improvement of error signal attenuation by over 7 dB, compared to a white noise excitation, also confirmed by automotive measurements. We present the necessary steps to identify dynamic automotive LEM systems to obtain traces of impulse responses for later reproducible tests of automotive hands-free systems. The method has been proposed to ITU-T standardization in focus group (FG) CARCOM.