Keyword extraction
Extract the important terms, entities, and themes from meeting transcripts — key people, organizations, technical terms, topics, and important numbers, grouped and structured. Runs on top of Minutes of Meetings.
What you get
Keyword extraction intelligently identifies the most important keywords and phrases in your transcribed Arabic content, giving you structured insight into the main themes discussed.
| Insight | Detail |
|---|---|
| Categorized keywords | Keywords grouped by semantic category — people, organizations, technical terms, topics, numbers. |
| Speaker keywords | Speaker-level keyword identification. |
| Temporal trends | How keywords rise and fall across the conversation. |
| Topic analysis | Topic insights and keyword statistics for deeper understanding. |
Typical use cases: meeting summaries and action-focused reporting; search indexing and content tagging; topic discovery across large audio archives.
How it works
This endpoint runs on top of a Minutes of Meetings transcription — process the meeting first, then extract.
| Step | What happens |
|---|---|
| 1 · Generate Minutes of Meeting | Process the meeting audio with Minutes of Meetings. |
| 2 · Use the transcription ID | Send the returned transcriptionId to Keyword Extraction. |
| 3 · Choose extraction depth | Pick basic, standard, or comprehensive. |
| 4 · Review results | Get structured keywords, topic insights, and trend analysis. |
Endpoint
Authenticated with the x-api-key header.
| Parameter | In | Type | Required | Description |
|---|---|---|---|---|
transcriptionId | path | string | Yes | ID from the Minutes of Meetings transcription. |
extraction_depth | body | string | No | basic, standard, or comprehensive. |
Extract keywords
Replace 805059bf-7c3f-4a1e-9d2b-1f0c6ae83b47 with the transcriptionId from your Minutes of Meetings run.
Response
Structured keywords plus the analysis around them. Extraction depth controls how much detail is populated.
| Field | What it holds |
|---|---|
keywords_by_category | Keywords grouped by semantic category. |
speaker_keywords | Keywords attributed to each speaker. |
keyword_trends | Temporal keyword trends across the conversation. |
topic_analysis | Topic insights derived from the keywords. |
keyword_statistics | Statistics for deeper understanding of the content. |
language | Detected language of the transcript. |
mixed_languages | Whether the content mixes languages. |
extraction_depth | The depth level the extraction ran at. |
processing_metadata | Metadata about the processing run. |
Go further
Keywords pair naturally with the rest of the understanding stack.
Working with an AI assistant? Every page is available as Markdown: add .md to the URL, or send an Accept: text/markdown header. For the whole documentation in one request, point it at llms-full.txt; the page index is llms.txt. Or use Copy Page, top right.
