most citedDiscriminatory and orthogonal feature learning for noise robust keyword spotting

6 citations · 6 across the 2 of their papers we have counts for

collaborators

3 papers

eess.AS2026

Parameter isolation with domain-specific experts for incremental audio classification

Jongyeon Park, Do-Hyeon Lim, Sang-won Park +4

To successfully deploy a model in time-varying environments such as streaming data prediction and sensing control, domain-incremental learning (DIL) has attracted attention since i…

eess.AS2026

Domain-incremental audio classification using domain-specific experts and prototype classifier

Jongyeon Park, Do-Hyeon Lim, Sang-won Park +4

This technical report presents submission systems for Task 7(domain-incremental audio classification) of the DCASE 2026 Challenge. The main obstacle is that, the system is unable t…

eess.AS2022★ 6 cited

Discriminatory and orthogonal feature learning for noise robust keyword spotting

Donghyeon Kim, Kyungdeuk Ko, David K. Han +1

Keyword Spotting (KWS) is an essential component in a smart device for alerting the system when a user prompts it with a command. As these devices are typically constrained by comp…