A Monte Carlo Search-Based Triplet Sampling Method for Learning Disentangled Representation of Impulsive Noise on Steering Gear

Seok Jun Bu, Namu Park, Gue Hwan Nam, Jae Yong Seo, Sung Bae Cho

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

6 Citations (Scopus)

Abstract

The classification task of impact noise on vehicle steering system mainly addresses the issue of modeling the transient and impulsive nature. Though various deep learning models including triplet network have been developed, the existing triplet network based on Euclidean distance metric is limited due to the simplicity of distance measure against reverberation generated from the narrow interior space and the low frequency difference generated from the interior finishes. In this paper, we propose a method to overcome the above two major hurdles by modify a sampling algorithm of triplet pairs based on structural similarity index instead of naive Euclidean distance within Monte Carlo based sampling strategy. We verify the proposed modified triplet loss through cross-validation that the proposed sampling method has more than 3% of accuracy improvement with computational cost reduction against the existing triplet networks. The detailed analysis shows that the proposed method can potentially compensate for the disjoint issues between the learning and validation vehicle types.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3057-3061
Number of pages5
ISBN (Electronic)9781509066315
DOIs
Publication statusPublished - 2020 May
Event2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain
Duration: 2020 May 42020 May 8

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2020-May
ISSN (Print)1520-6149

Conference

Conference2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Country/TerritorySpain
CityBarcelona
Period20/5/420/5/8

Bibliographical note

Funding Information:
This research was supported by Hyundai Mobis.

Publisher Copyright:
© 2020 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A Monte Carlo Search-Based Triplet Sampling Method for Learning Disentangled Representation of Impulsive Noise on Steering Gear'. Together they form a unique fingerprint.

Cite this