most citedAC-Mix: Self-Supervised Adaptation for Low-Resource Automatic Speech Recognition using Agnostic Contrastive Mixup

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eess.AS2025

Group-Aware Partial Model Merging for Children's Automatic Speech Recognition

Thomas Rolland, Alberto Abad

While supervised fine-tuning of adult pre-trained models for children's ASR has shown promise, it often fails to capture group-specific characteristics and variations among childre…

eess.AS2024★ 1 cited

AC-Mix: Self-Supervised Adaptation for Low-Resource Automatic Speech Recognition using Agnostic Contrastive Mixup

Carlos Carvalho, Alberto Abad

Self-supervised learning (SSL) leverages large amounts of unlabelled data to learn rich speech representations, fostering improvements in automatic speech recognition (ASR), even w…