Multichannel End-to-end Speech Recognition
Table 1: Character error rate [%] for CHiME-4 corpus.
['model', 'dev simu', 'dev real', 'eval simu', 'eval real']
NOISY and BEAMFORMIT were the baseline single-channel end-to-end systems, which did not include the speech enhancement part in their frameworks. During decoding, NOISY used single-channel noisy speech data from ’isolated 1ch track’ in CHiME-4 as an input, while BEAMFORMIT used the enhanced speech data obtained from 5-channel signals with BeamformIt The comparison of MASK_NET (REF) and MASK_NET (ATT) validates the use of the attention-based mechanism for reference selection. Finally, MASK_NET (ATT) achieved better recognition performance than BEAMFORMIT, which proves the effectiveness of our joint integration rather than a pipe-line combination of speech enhancement and (end-to-end) speech recognition.