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This paper introduces effective design choices for text-to-music retrievalsystems. An ideal text-based retrieval system would support various inputqueries such as pre-defined tags, unseen tags, and sentence-level descriptions.In reality, most previous works mainly focused on a single query type (tag orsentence) which may not generalize to another input type. Hence, we reviewrecent text-based music retrieval systems using our proposed benchmark in twomain aspects: input text representation and training objectives. Our findingsenable a universal text-to-music retrieval system that achieves comparableretrieval performances in both tag- and sentence-level inputs. Furthermore, theproposed multimodal representation generalizes to 9 different downstream musicclassification tasks. We present the code and demo online.

Toward Universal Text-to-Music Retrieval