Individual Channels Signal Enhancement

Prior to doing any multichannel beamforming each individual channel is Wiener filtered (Wiener and Norbert, 1949). It aims at cleaning the signal from corrupting noise, which is considered to be additive and of a stochastic nature. The Wiener filter parameters $w(t)$ are chosen so that the mean square error between the clean signal $x(t)$ and the resulting output signal $s(t)$ is minimized. Considering an additive noise $n(t)$ it can be written as:

$$x_{n}[k] = w_{n}[k] * (s_{N}[k] + n_{n}[k])$$ (5.6)

where $s_{n}[k]$ and $n_{n}[k]$ are the discrete speech and noise recorded by each of the $N$ channels in the room, and $x_{n}[k]$ is the cleaned signal which will be further processed by the system.

In this implementation Wiener filtering is applied to each channel independently, not taking advantage of the multichannel properties of the speech or noise being recorded as in Rombouts and M.Moonen (2003) and Doclo and Moonen (2002). Being that the microphones are located in unknown places in the room it is considered that no assumptions can be made on the noise or speech properties at this level. The Wiener filtering implementation is taken from ICSI-SRI-UW and used in the ASR system as explained in Mirghafori et al. (2004).