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.
Ssvd: Structured svd for parameter-efficient fine-tuning and benchmarking under domain shift in asr,
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A PECL method for ASR partitions weight matrices via singular values, adapts only via rotations in the tail subspace, and averages rotations across tasks to reduce forgetting while outperforming baselines on two benchmarks.
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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.
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Parameter-Efficient Continual Learning for Automatic Speech Recognition
A PECL method for ASR partitions weight matrices via singular values, adapts only via rotations in the tail subspace, and averages rotations across tasks to reduce forgetting while outperforming baselines on two benchmarks.