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Temporal Grounding Demo

Navigate over to the video-transcription playground in our playground to see the temporal grounding in action.
Temporal grounding is a powerful capability of VLM Run that links extracted data to precise time segments within audio and video content. This feature is especially valuable for applications that need to process and analyze time-based media—such as podcasts, interviews, lectures, and meetings—by providing structured, timestamped insights. Temporal grounding can be broadly categorized into two key functions:
  1. Time Segmentation: Dividing content into meaningful segments, each with precise start and end timestamps.
  2. Content Localization: Pinpointing exactly when and where specific information appears within the timeline.

Using Temporal Grounding

Temporal grounding when processing audio/video content is enabled by default for all audio/video domains.

Understanding the Output

The response includes temporal information for each extracted segment, including start and end times, speaker identification, and confidence scores:
If you want to test the grounding precision of our models, you can go to the VLM Run Platform and click on the start_time and end_time of any of the segments to skip to the corresponding audio/video segments.

Use Cases

Temporal grounding enables numerous applications:
  1. Searchable Media Archives: Create searchable indexes of audio and video content
  2. Meeting Summaries: Generate timestamped summaries of meetings with speaker attribution
  3. Content Navigation: Build interfaces that allow users to jump to specific topics or speakers
  4. Podcast Production: Automatically generate show notes with timestamps and speaker labels
  5. Video Chapters: Create chapter markers for long-form video content
  6. Interview Analysis: Extract insights from interviews with accurate speaker attribution
  7. Compliance Monitoring: Track who said what and when in regulated communications
By leveraging VLM Run’s temporal grounding capabilities, you can extract rich, time-based structured data from audio and video content, enabling powerful applications that understand not just what was said, but who said it and when.

Try our Video / Audio -> JSON API today

Head over to our Video -> JSON or Audio -> JSON to start building your own video/audio processing pipelines with VLM Run. Sign-up for access on our platform.