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Table 1: PER (%) on the TIMIT development and test sets. The upper panel reports the results of various ANN and SNN architectures from the literatures, and the lower panel presents the results achieved by the ANN and SNN models in this work (AM: acoustic model, *: the best result to date).
['FeaturesAM', 'Test Li-GRU(Ravanelli et\xa0al.,  2018 )', 'Test Li-GRU(Ravanelli et\xa0al.,  2018 )', 'Test RSNN(Bellec et\xa0al.,  2019 )', 'Test RSNN(Bellec et\xa0al.,  2019 )']
ASR performances of other state-of-the-art systems using various ANN and SNN architectures are given in the upper panel for reference purposes. In particular, the ANN system trained with the standard 13-dimensional FBANK feature achieves the best PER of 16.9% (18.5%) on the development (test) set. The equivalent SNN system using the same feature achieves slightly worse PER of 17.3% (18.7%) on the development (test) set.