arxivcs.SDcs.AIeess.AS2026-06-27
ALM2Vec: Learning Audio Embeddings for Universal Audio Retrieval with Large Audio-Language Models
Fengjie Lu, Chenang Jiang, Jiarui Hai, Helin Wang, Aaron Yee
Recent advances in language--audio retrieval have been largely driven by contrastive dual-encoder architectures that align audio and text in a shared embedding space. While effective, existing retrieval embeddings are primarily optimized for audio--caption matching, limiting thei…