Papers › Attention-Free Keyword Spotting

Attention-Free Keyword Spotting

14 Oct 2021arXiv:2110.07749archive 2025-07-28

Mashrur M. Morshed, Ahmad Omar Ahsan

Till now, attention-based models have been used with great success in the keyword spotting problem domain. However, in light of recent advances in deep learning, the question arises whether self-attention is truly irreplaceable for recognizing speech keywords. We thus explore the usage of gated MLPs --previously shown to be alternatives to transformers in vision tasks-- for the keyword spotting task. We provide a family of highly efficient MLP-based models for keyword spotting, with less than 0.5 million parameters. We show that our approach achieves competitive performance on Google Speech Commands V2-12 and V2-35 benchmarks with much fewer parameters than self-attention-based methods.

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