Exploring Filterbank Learning for Keyword Spotting

@article{LopezEspejo2021ExploringFL,
  title={Exploring Filterbank Learning for Keyword Spotting},
  author={Iv'an L'opez-Espejo and Z. Tan and Jesper H{\o}jvang Jensen},
  journal={2020 28th European Signal Processing Conference (EUSIPCO)},
  year={2021},
  pages={331-335}
}
Despite their great performance over the years, handcrafted speech features are not necessarily optimal for any particular speech application. Consequently, with greater or lesser success, optimal filterbank learning has been studied for different speech processing tasks. In this paper, we fill in a gap by exploring filterbank learning for keyword spotting (KWS). Two approaches are examined: filterbank matrix learning in the power spectral domain and parameter learning of a psychoacoustically… 
Deep Spoken Keyword Spotting: An Overview
TLDR
The analysis performed in this paper allows us to identify a number of directions for future research, including directions adopted from automatic speech recognition research and directions that are unique to the problem of spoken KWS.

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