Connect speech to visual context
Select recordings where the audio and picture describe the same event. Confirm source relationships and timing information in a representative sample.
FIUND / Multimodal AI
Explore connected audio and video for models that interpret speech, people and visual context. Source relationships, sequence boundaries and agreed annotations matter as much as the individual files.
Conversation context
Boundaries · roles · overlap
Language · timestamps · text
Model tasks
Select recordings where the audio and picture describe the same event. Confirm source relationships and timing information in a representative sample.
Specify whether the task needs full sessions, continuous scenes or bounded clips. Preserve the context around an interaction rather than selecting isolated highlights.
Define the questions or behaviors your model should handle. Agree which transcripts, timestamps and visual annotations support that assessment.
Explore the source formats and context that could support your task. Access and suitability are confirmed for each proposed project.
Scope before scale
Original recordings, combined views, individual tracks and the identifiers linking them.
Sequence length, timestamps, edits, offsets and synchronization requirements.
Transcript coverage, task labels and other annotations required for your model.
Sample review
Review the published collection scope, then request a sample for your intended evaluation. Other sources and annotations are scoped separately.
Synchronization should be checked for the selected source and intended task. Required alignment tolerances and any preparation are agreed for the project.
Specify the views and audio tracks you need. Available source components and delivery formats are confirmed for the proposed collection.
Only annotations listed in the agreed scope are included. New labeling requirements are discussed separately from the source recordings.