Conjoint Audio-to-Spikes Encoding and Processing for Efficient Neuromorphic Speech Recognition
This work introduces the first end-to-end neuromorphic spike-encoding and evaluation of the TIMIT dataset and quantifies the pipeline's efficiency with hardware-agnostic metrics based on the quantitative spiking activity.
Valentin Meunier, Amélie Gruel, Pierre Lewden et al.
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