7 citations · 17 across the 21 of their papers we have counts for
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cs.SD2024★ 1 cited
Enhancing Audio-Language Models through Self-Supervised Post-Training with Text-Audio Pairs
Anshuman Sinha, Camille Migozzi, Aubin Rey +1
Research on multi-modal contrastive learning strategies for audio and text has rapidly gained interest. Contrastively trained Audio-Language Models (ALMs), such as CLAP, which esta…
cs.SD2024
Can Large Language Models Understand Spatial Audio?
Changli Tang, Wenyi Yu, Guangzhi Sun +8
This paper explores enabling large language models (LLMs) to understand spatial information from multichannel audio, a skill currently lacking in auditory LLMs. By leveraging LLMs'…