Replacing standard attention with gated focused linear attention makes speech separation models run faster and use less memory while keeping separation quality close to the state of the art.
Dataset We validate our model’s performance using four popular speech separation datasets: WSJ0-2Mix [3], WHAM! [28], WHAMR! [29], and Libri2Mix [30]
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FLASepformer: Efficient Speech Separation with Gated Focused Linear Attention Transformer
Replacing standard attention with gated focused linear attention makes speech separation models run faster and use less memory while keeping separation quality close to the state of the art.