Annotation for Audio-Visual Sound Localization

Label when a sound occurs and where its visible source appears. Review related audio and visual recordings together, using consistent source properties to preserve the correspondence.
Audio-visual collage showing a labeled bell and an audio interval with matching source identifiers.

Build Datasets That Connect Sound and Sight

Prepare examples with explicit audible events, visible source regions and reviewed correspondence.
A bell-ringing interval is marked on an audio waveform with a source identifier.

Sound Event Intervals

Mark the audible event’s start and end in the recording. Use a defined sound class, such as bell ringing, and preserve the waveform context around the interval.
A visual source box marks a desk bell and records its source identifier.

Visible Sound Sources

Annotate the object that produces the audible event when it is visible in the corresponding frame. Keep the source boundary tight and use consistent visual classes.
Related bell image and audio annotations use matching source identifiers for review.

Reviewed Source Correspondence

Review related audio and visual inputs together. Apply matching source identifiers or event properties after checking the correspondence against the recordings.
An audio interval and bell source identifier are inspected in a review step.

Boundary and Source Review

Check the audio interval, visual object and source properties during review. Correct uncertain boundaries or inconsistent source labels before the example is accepted.

Why AI Teams Choose Unitlab

Keep source data, annotation rules and review decisions connected as your team prepares audio-visual sound localization.
15X
Faster Data Annotation
60%
Free Up AI Engineers’ Time
5X
Lower AI Development Costs

Annotation Types for Audio-Visual Localization

Represent the audible event and its visible source using the native tools for each recording.
A bell-ringing interval is marked on an audio waveform with a source identifier.

Audio Intervals

Bounded time intervals identify where a defined sound event occurs. Class and property values describe the audible evidence without replacing the recording.

Visual Source Boxes

Bounding boxes identify the visible source in an image or video frame. Review the source box with the corresponding audio evidence and configured properties.

A visual source box marks a desk bell and records its source identifier.

Audio-Visual Sound Localization FAQs

What is audio-visual sound localization annotation?

It prepares examples that identify a sound event and its visible source. Annotators label the audible interval and the relevant object in related visual media, then review their correspondence.

How does it differ from sound event detection?

Sound event detection identifies what is heard and when. Audio-visual localization also identifies the source visible in the scene, such as the bell producing a ringing sound.

Can audio and video be opened together?

Supported audio and video files can be grouped in a multimodal case. A configured layout keeps the related sources available while annotators use each viewer’s native tools.

How is correspondence recorded across sources?

Teams can use matching configured source identifiers or event properties on the relevant annotations. Annotators inspect the recordings to establish correspondence; grouping does not infer that an audible event belongs to an object.

Does file grouping synchronize recordings automatically?

File grouping organizes related inputs using configured naming rules and keys. Teams must verify their timing and recording correspondence before labeling a sound source.

What if the source is not visible?

Define a project rule for off-screen or uncertain sources and record that condition with a configured property. A visible-source box should only be created when the object is supported by the frame.

Can several sounds be labeled in one recording?

Annotators can create separate intervals for the events required by the ontology. Clear definitions and review are especially useful when sounds overlap or a source is ambiguous.

Is sound localization generated automatically?

This workflow prepares human-labeled examples and reviewed source correspondence. The annotations support downstream model training and evaluation; they are not a claim that Unitlab automatically localizes sound.

How is localization annotation reviewed?

Reviewers check the audible boundaries, visible source region and configured identifiers against the related recordings. Rejected work can return for correction before acceptance.