  Language-based audio retrieval is a task, where natural language textual
captions are used as queries to retrieve audio signals from a dataset. It has
been first introduced into DCASE 2022 Challenge as Subtask 6B of task 6, which
aims at developing computational systems to model relationships between audio
signals and free-form textual descriptions. Compared with audio captioning
(Subtask 6A), which is about generating audio captions for audio signals,
language-based audio retrieval (Subtask 6B) focuses on ranking audio signals
according to their relevance to natural language textual captions. In DCASE
2022 Challenge, the provided baseline system for Subtask 6B was significantly
outperformed, with top performance being 0.276 in mAP@10. This paper presents
the outcome of Subtask 6B in terms of submitted systems' performance and
analysis.
