Robust joint multi-microphone parameter based on simultaneous confirmatory factor analysis

One of the biggest challenges in multimicrophone applications is the estimation of the parameters of the signal model, such as the power spectral densities (PSDs) of the sources, the early (relative) acoustic transfer functions of the sources with respect to the microphones, the PSD of late reverberation, and the PSDs of microphone-self noise. Typically, existing methods estimate subsets of the aforementioned parameters and assume some of the other parameters to be known a priori. This may result in inconsistencies and inaccurately estimated parameters and potential performance degradation in the applications using these estimated parameters. So far, there was no method to jointly estimate all the aforementioned parameters. In this software with corresponding articles,

A.I. Koutrouvelis, R.C. Hendriks, R. Heusdens & J. Jensen, "Robust Joint Estimation of Multi-Microphone Signal Model Parameters." IEEE/ACM Trans. on Audio, Speech, and Lang. Proc., 27(7), 1136-1150, 2019.

and

A.I. Koutrouvelis, R.C. Hendriks, R. Heusdens & J. Jensen, "Estimation of Sensor Array Signal Model Parameters Using Factor Analysis." EUSIPCO, 2019.

we propose a robust method for jointly estimating all the aforementioned parameters using confirmatory factor analysis. The estimation accuracy of the signal-model parameters thus obtained outperforms existing methods in most cases. We experimentally show significant performance gains in several multimicrophone applications over state-of-the-art methods.

Related publications

  1. Robust Joint Estimation of MultiMicrophone Signal Model Parameters
    Andreas I. Koutrouvelis; Richard C. Hendriks; Richard Heusdens; Jesper Jensen;;
    Trans. Audio, Speech and Language Processing,
    Volume 27, Issue 7, pp. 1136 - 1150, July 2019.
    document

  2. Estimation of Sensor Array Signal Model Parameters Using Factor Analysis
    Andreas I. Koutrouvelis ; Richard C. Hendriks; Richard Heusdens; Jesper Jensen;
    In 27th European Signal Processing Conference (EUSIPCO 2019),
    2019.
    document

Repository data

File: SCFA.zip
Size: 13 kB
Modified: 20 December 2019
Type: software
Authors: Richard Hendriks, Richard Heusdens, Andreas Koutrouvelis
Date: December 2019
Contact: Richard Hendriks