Music Transcription
Residual Shuffle-Exchange Network
Introduced by Draguns et al. in Residual Shuffle-Exchange Networks for Fast Processing of Long SequencesResidual Shuffle-Exchange Network is an efficient alternative to models using an attention mechanism that allows the modelling of long-range dependencies in sequences in O(n log n) time. This model achieved state-of-the-art performance on the MusicNet dataset for music transcription while being able to run inference on a single GPU fast enough to be suitable for real-time audio processing.
Source: Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences
Papers
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RSU Beneš Block
