- K. Kumatani, B. Raj, Rita Singh, J. McDonough. 2012. Microphone Array Post-filter based on Spatially-Correlated Noise Measurements for Distant Speech Recognition. Abstract: This paper presents a new microphone-array post-ﬁltering algorithm for distant speech recognition (DSR). Convention-ally, post-ﬁltering methods assume static noise ﬁeld models, and using this assumption, employ a Wiener ﬁlter mechanism for estimating the noise parameters. In contrast to this, we show how we can build the Wiener post-ﬁlter based on actual noise observations without any noise-ﬁeld assumption. The algorithm is framed within a state-of-the-art beamforming technique, namely maximum negentropy (MN) beamforming with super directivity. We investigate the effectiveness of the proposed post-ﬁlter on DSR through experiments on noisy data collected in a car under different acoustic conditions. Experiments show that the new post-ﬁltering mechanism is able to achieve up to 20% relative reduction of word error rates (WER) under the represented noise conditions, as compared to a single distant microphone. In contrast, super-directive (SD) beamforming followed by Zelinski post-ﬁltering achieves a relative WER reduction of only up to 11%. Other post-ﬁlters evaluated perform similarly in comparison to the proposed post-ﬁlter.
