Effective Integration of KAN for Keyword Spotting

Anfeng Xu; Biqiao Zhang; Shuyu Kong; Yiteng Huang; Zhaojun Yang; Sangeeta Srivastava; Ming Sun

doi:10.1109/icassp49660.2025.10890453

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arXiv · 2409.08605

Effective Integration of KAN for Keyword Spotting

Anfeng Xu·Biqiao Zhang·Shuyu Kong·Yiteng Huang·Zhaojun Yang·Sangeeta Srivastava·Ming Sun

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Abstract

Keyword spotting (KWS) is an important speech processing component for smart devices with voice assistance capability. In this paper, we investigate if Kolmogorov-Arnold Networks (KAN) can be used to enhance the performance of KWS. We explore various approaches to integrate KAN for a model architecture based on 1D Convolutional Neural Networks (CNN). We find that KAN is effective at modeling high-level features in lower-dimensional spaces, resulting in improved KWS performance when integrated appropriately. The findings shed light on understanding KAN for speech processing tasks and on other modalities for future researchers.

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Anfeng Xu, Biqiao Zhang, Shuyu Kong, Yiteng Huang, Zhaojun Yang, Sangeeta Srivastava, Ming Sun. 2024-09-13. Effective Integration of KAN for Keyword Spotting. https://doi.org/10.1109/icassp49660.2025.10890453

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