The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation
Ilaria Manco
Benno Weck
Seungheon Doh
Minz Won
Yixiao Zhang
Dmitry Bodganov
Yusong Wu
Ke Chen
Philip Tovstogan
Emmanouil Benetos
Elio Quinton
Gyorgy Fazekas
Juhan Nam

Abstract
We introduce the Song Describer dataset (SDD), a new crowdsourced corpus of high-quality audio-caption pairs, designed for the evaluation of music-and-language models. The dataset consists of 1.1k human-written natural language descriptions of 706 music recordings, all publicly accessible and released under Creative Common licenses. To showcase the use of our dataset, we benchmark popular models on three key music-and-language tasks (music captioning, text-to-music generation and music-language retrieval). Our experiments highlight the importance of cross-dataset evaluation and offer insights into how researchers can use SDD to gain a broader understanding of model performance.
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