Audio material in archives, museums and heritage collections often contains valuable information: interviews, oral history, lectures, radio material or event recordings. At the same time, audio is often difficult to access. Long recordings take time to listen to and important passages are not always easy to find. With Audio segmentation, sound material is divided into separate meaningful parts, for example by speakers, topics, silences, transitions or content fragments.

From long recording to usable fragments

Audio segmentation divides sound recordings into smaller recognisable parts. A recording is no longer approached only as a whole, but as a series of fragments with their own content and meaning.

Better access to audio collections

By dividing audio into segments, specific passages, topics or voices become easier to find. This makes sound material more searchable and accessible.

Support for description and enrichment

Segmented audio provides a strong basis for further access. Fragments can be linked individually to timecodes, transcripts, keywords or additional metadata.

Valuable for research and selection

Audio segmentation helps you select, compare and analyse relevant passages without listening to full recordings each time.

Suitable for many types of audio material

Audio segmentation can be used for interviews, oral history, lectures, radio material, field recordings and other audio collections.

A complement to human expertise

AI helps recognise structure, speakers and transitions, while substantive assessment and refinement remain with the people who know the material.

What it delivers

More overview in audio collections
Bring structure to long or complex recordings and make material easier to manage.

Find relevant passages faster
Search audio more precisely and find the fragments that matter.

Richer metadata and better access
Use segments as a basis for transcription, annotation and more precise description.

More usability for research and presentation
Make audio material easier to use for collection research, education and public projects.

Human in the loop

In audiovisual heritage, context is indispensable. AI helps add structure and identify segments, but substantive review and interpretation remain with researchers, archivists and collection managers.