15 citations · 29 across the 6 of their papers we have counts for
6 papers · 1 filter
Towards Privacy-Preserving ASR: Speaker-Level Machine Unlearning
Seaone Ok, Seungu Han, Eungbeom Kim +1
Automatic Speech Recognition (ASR) systems are commonly designed to transcribe linguistic content independently of speaker identity. However, speaker-specific information can persi…
Fast Speech Foundation Model Distillation Using Interleaved Stacking
Eungbeom Kim, Kyogu Lee
Distilling a large speech foundation model (SFM) into an efficient student model has been successfully applied to low-resource environments. Although distillation reduces inference…
Cross-Modal Bottleneck Fusion For Noise Robust Audio-Visual Speech Recognition
Seaone Ok, Min Jun Choi, Eungbeom Kim +2
Audio-Visual Speech Recognition (AVSR) leverages both acoustic and visual cues to improve speech recognition under noisy conditions. A central question is how to design a fusion me…
Guiding Frame-Level CTC Alignments Using Self-knowledge Distillation
Eungbeom Kim, Hantae Kim, Kyogu Lee
Transformer encoder with connectionist temporal classification (CTC) framework is widely used for automatic speech recognition (ASR). However, knowledge distillation (KD) for ASR d…
Debiased Automatic Speech Recognition for Dysarthric Speech via Sample Reweighting with Sample Affinity Test
Eungbeom Kim, Yunkee Chae, Jaeheon Sim +1
Automatic speech recognition systems based on deep learning are mainly trained under empirical risk minimization (ERM). Since ERM utilizes the averaged performance on the data samp…
Representation Selective Self-distillation and wav2vec 2.0 Feature Exploration for Spoof-aware Speaker Verification
Jin Woo Lee, Eungbeom Kim, Junghyun Koo +1
Text-to-speech and voice conversion studies are constantly improving to the extent where they can produce synthetic speech almost indistinguishable from bona fide human speech. In…