TY - JOUR
T1 - A Class of Optimal Rectangular Filtering Matrices for Single-Channel Signal Enhancement in the Time Domain
AU - Jensen, Jesper Rindom
AU - Benesty, Jacob
AU - Christensen, Mads Græsbøll
AU - Chen, Jingdong
PY - 2013
Y1 - 2013
N2 - In this paper, we introduce a new class of op- timal rectangular filtering matrices for single-channel speech enhancement. The new class of filters exploits the fact that the dimension of the signal subspace is lower than that of the full space. By doing this, extra degrees of freedom in the filters, that are otherwise reserved for preserving the signal subspace, can be used for achieving an improved output signal-to-noise ratio (SNR). Moreover, the filters allow for explicit control of the tradeoff between noise reduction and speech distortion via the chosen rank of the signal subspace. An interesting aspect is that the framework in which the filters are derived unifies the ideas of optimal filtering and subspace methods. A number of different optimal filter designs are derived in this framework, and the properties and performance of these are studied using both synthetic, periodic signals and real signals. The results show a number of interesting things. Firstly, they show how speech distortion can be traded for noise reduction and vice versa in a seamless manner. Moreover, the introduced filter designs are capable of achieving both the upper and lower bounds for the output SNR via the choice of a single parameter.
AB - In this paper, we introduce a new class of op- timal rectangular filtering matrices for single-channel speech enhancement. The new class of filters exploits the fact that the dimension of the signal subspace is lower than that of the full space. By doing this, extra degrees of freedom in the filters, that are otherwise reserved for preserving the signal subspace, can be used for achieving an improved output signal-to-noise ratio (SNR). Moreover, the filters allow for explicit control of the tradeoff between noise reduction and speech distortion via the chosen rank of the signal subspace. An interesting aspect is that the framework in which the filters are derived unifies the ideas of optimal filtering and subspace methods. A number of different optimal filter designs are derived in this framework, and the properties and performance of these are studied using both synthetic, periodic signals and real signals. The results show a number of interesting things. Firstly, they show how speech distortion can be traded for noise reduction and vice versa in a seamless manner. Moreover, the introduced filter designs are capable of achieving both the upper and lower bounds for the output SNR via the choice of a single parameter.
KW - Noise reduction
KW - signal enhancement
KW - time-domain filtering
KW - maximum SNR filtering matrix
KW - Wiener filtering matrix
KW - MVDR filtering matrix
KW - tradeoff filtering matrix
U2 - 10.1109/TASL.2013.2280215
DO - 10.1109/TASL.2013.2280215
M3 - Journal article
SN - 1558-7916
VL - 21
SP - 2595
EP - 2606
JO - I E E E Transactions on Audio, Speech and Language Processing
JF - I E E E Transactions on Audio, Speech and Language Processing
IS - 12
ER -