A Lightweight Dynamic Filter For Keyword Spotting

Donghyeon Kim, Kyungdeuk Ko, Jeonggi Kwak, David K. Han, Hanseok Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Keyword Spotting (KWS) from speech signals is widely applied to perform fully hands-free speech recognition. The KWS network is designed as a small-footprint model so it can continuously be active. Recent efforts have explored dynamic filter-based models in deep learning frameworks to enhance the system's robustness or accuracy. However, as a dynamic filter framework requires high computational costs, the implementation is limited to the computational condition of the device. In this paper, we propose a lightweight dynamic filter to improve the performance of KWS. Our proposed model divides the dynamic filter into two branches to reduce computational complexity: pixel level and instance level. The proposed lightweight dynamic filter is applied to the front end of KWS to enhance the separability of the input data. The experimental results show that our model is robustly working on unseen noise and small training data environments by using a small computational resource.

Original languageEnglish
Title of host publicationICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350302615
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, ICASSPW 2023 - Rhodes Island, Greece
Duration: 2023 Jun 42023 Jun 10

Publication series

NameICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings

Conference

Conference2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, ICASSPW 2023
Country/TerritoryGreece
CityRhodes Island
Period23/6/423/6/10

Bibliographical note

Funding Information:
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Exotic Invasive Species Management Program, funded by Korea Ministry of Environment(MOE) (2021002280004) David Han’s work on this paper is partly sponsored by the Office of Naval Research (.Grant Number: N00014-21-1-2790.).

Publisher Copyright:
© 2023 IEEE.

Keywords

  • computational cost
  • dynamic filter
  • dynamic weight
  • keyword spotting

ASJC Scopus subject areas

  • Computer Science Applications
  • Acoustics and Ultrasonics
  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

Fingerprint

Dive into the research topics of 'A Lightweight Dynamic Filter For Keyword Spotting'. Together they form a unique fingerprint.

Cite this