TY - JOUR
T1 - Robust Joint Estimation of Multimicrophone Signal Model Parameters
AU - Koutrouvelis, Andreas I.
AU - C. Hendriks, Richard
AU - Heusdens, Richard
AU - Jensen, Jesper
PY - 2019/7
Y1 - 2019/7
N2 - 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 is no method to jointly estimate all the aforementioned parameters. In this paper, 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.
AB - 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 is no method to jointly estimate all the aforementioned parameters. In this paper, 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.
KW - Confirmatory factor analysis
KW - dereverberation
KW - joint diagonalization
KW - multimicrophone
KW - source separation
KW - speech enhancement
UR - http://www.scopus.com/inward/record.url?scp=85065558712&partnerID=8YFLogxK
U2 - 10.1109/TASLP.2019.2911167
DO - 10.1109/TASLP.2019.2911167
M3 - Journal article
SN - 2329-9290
VL - 27
SP - 1136
EP - 1150
JO - IEEE/ACM Transactions on Audio, Speech, and Language Processing
JF - IEEE/ACM Transactions on Audio, Speech, and Language Processing
IS - 7
M1 - 8691792
ER -