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    "readmeSummary": "## Video & Audio Transcriber\n\nConverts public audio and video into searchable, timestamped transcripts and subtitle files for captioning, archives, research, and AI workflows. Processes single media links, podcast feeds, or batches to produce plain transcript text, timed segments with start/end timestamps, subtitle content in SRT and WebVTT formats, language metadata with confidence, duration and source metadata (title, resolved URL, platform classification), and processing metadata (chosen speech model and task mode: transcription or translation). Supports automatic language detection or explicit language selection and multiple speech-model sizes tuned for different accuracy/runtime trade-offs. Batch processing preserves per-item outcomes so successful items are returned alongside item-level error records. Outputs are oriented toward caption generation, searchable text archives, editorial and research workflows, and downstream AI ingestion (retrieval, summarization, vectorization).\n\n## Use cases\n\n- Create captions and subtitle drafts for public video.\n- Prepare searchable archives of spoken content for content and video teams.\n- Produce notes and transcripts from public interviews, lectures, and recordings for researchers and journalists.\n- Convert recent public podcast episodes into text for editorial planning and podcast teams.\n- Supply speech-derived text to AI pipelines for retrieval, analysis, or summarization.\n- Index spoken interviews, calls, lectures, and meetings that are publicly shared.\n- Export timestamped transcript segments and subtitle files for captioning and downstream processing.\n- Maintain traceability by keeping source links and metadata with each transcript.",
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