Natural English Dialogue Sets
Natural multi-speaker conversation with the turn structure, timing and speaker context needed for ASR, diarisation and conversational systems.
View datasetAmbient recordings are much more useful when the conditions that produced them remain visible. Acoustic Environment Sets organise audio around the scene, device and environmental context that matter to the modelling task.
Where individual sound events are important, they can also be represented on the timeline so scene-level context and event-level information coexist in the same collection. This allows a model to work with both the broader acoustic environment and the specific sounds occurring within it.
Acoustic scene classification, sound-event detection, environmental audio modelling and speech-system robustness.
Scene taxonomy, recording conditions and event granularity are defined around the target acoustic problem.
The exact package depends on the collection scope. Where relevant, delivery can include task-specific records, manifests, provenance fields, stable identifiers, SHA-256 hashes, MLCommons Croissant 1.0 metadata and loading instructions.