Robust Multi-channel Speech Recognition using Frequency Aligned Network
Table 2: Word Error Rate Reduction relative to Raw-1ch model
['[BOLD] Raw-2ch', 'dev', '[BOLD] Set1 noPB 6.92', '[BOLD] Set1 PB 10.71', '[BOLD] Set2 PB 5.98', '[BOLD] Total  [BOLD] 6.36']
We can see that the improvement from FAN and average pooling is on Set1 PB, while Set2 PB has slightly better WERR over Set1 noPB. This contrasts to BAT-AT model’s improvement in Set1 PB and Set2 PB since the improvements are less concentrated on the utterances with playback echo. According to this experimental results, the proposed FAN architecture followed by average pooling gives even more benefit to the utterances with intense noise.