Gumbel-BEARD automates Whisper layer selection with Gumbel-Softmax and BEST-RQ for self-supervised domain adaptation, matching fully supervised performance on 10h vs 133h data and setting new SOTA WERs on MyST and OGI datasets.
The Corpus of Regional African American Language,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
eess.AS 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
GC-LoRA introduces a gated convolutional adapter into LoRA for efficient adaptation of transformer speech models to domain-specific acoustics, reporting up to 10.9% WER reduction on diverse test sets.
citing papers explorer
-
Gumbel-BEARD: Automatic Layer Selection for Self-Supervised Adaptation of Whisper in Low-Resource Domains
Gumbel-BEARD automates Whisper layer selection with Gumbel-Softmax and BEST-RQ for self-supervised domain adaptation, matching fully supervised performance on 10h vs 133h data and setting new SOTA WERs on MyST and OGI datasets.
-
GC-LoRA: Gated Convolutional LoRA for Parameter-Efficient Acoustic Adaptation
GC-LoRA introduces a gated convolutional adapter into LoRA for efficient adaptation of transformer speech models to domain-specific acoustics, reporting up to 10.9% WER reduction on diverse test sets.