Contrastive Audio-Language Learning for Music. (arXiv:2208.12208v1 [cs.SD])

As one of the most intuitive interfaces known to humans, natural language has
the potential to mediate many tasks that involve human-computer interaction,
especially in application-focused fields like Music Information Retrieval. In
this work, we explore cross-modal learning in an attempt to bridge audio and
language in the music domain. To this end, we propose MusCALL, a framework for
Music Contrastive Audio-Language Learning. Our approach consists of a
dual-encoder architecture that learns the alignment between pairs of music
audio and …

arxiv audio language learning music