Dec 22, 2023 · We introduce Multimodal Attention Merging (MAM), an attempt that facilitates direct knowledge transfer from attention matrices of models rooted in high ...
We apply attention merging to two tasks: Automatic Speech. Recognition (ASR) and Audio Event Classification (AEC). ASR transcribes human speech to text ...
We apply attention merging to two tasks: Automatic Speech. Recognition (ASR) and Audio Event Classification (AEC). ASR transcribes human speech to text ...
Multimodal model merging is a strategy to merge models trained on different tasks to generate a generalized multi-task architecture capable of processing ...
Sep 28, 2024 · This chapter demonstrates how multimodal fusion can be implemented in practice and how multimodal analysis can lead to better results than just ...
Feb 9, 2024 · Training large foundation models using self-supervised objectives on unlabeled data, followed by fine-tuning on downstream tasks, ...
Training large foundation models using self-supervised objectives on unlabeled data, followed by fine-tuning on downstream tasks, has emerged as a standard ...
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Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification · no code implementations • 22 Dec 2023 • Anirudh S. Sundar, ...
Training Early-Exit Architectures for Automatic Speech Recognition ... Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification.
2024. Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification. AS Sundar, CHH Yang, DM Chan, S Ghosh, V Ravichandran ...