  Automated Audio Captioning is a cross-modal task, generating natural language
descriptions to summarize the audio clips' sound events. However, grounding the
actual sound events in the given audio based on its corresponding caption has
not been investigated. This paper contributes an AudioGrounding dataset, which
provides the correspondence between sound events and the captions provided in
Audiocaps, along with the location (timestamps) of each present sound event.
Based on such, we propose the text-to-audio grounding (TAG) task, which
interactively considers the relationship between audio processing and language
understanding. A baseline approach is provided, resulting in an event-F1 score
of 28.3% and a Polyphonic Sound Detection Score (PSDS) score of 14.7%.
