New Features
- Added WhisperLargeV3Ct2, a high-quality speech-to-text model.
- Supports multiple timestamp levels, confidence scores, and optional speaker diarization.
- New output formats include:
plain.json: Transcript text without timestamps
seg.json: Timestamped segments
word.json: Word-level timestamps and confidence scores
seg_diar.json: Timestamped segments with speaker labels
word_diar.json: Word-level timestamps with speaker labels
transcript.txt: Plain readable transcript
- Responses can include detected
language, language_probability, timestamp level, segment confidence, and speaker IDs.
YouTube & TikTok Metadata
- Optional source metadata can be requested when transcribing YouTube or TikTok URLs for an additional fee of $0.005 per request.
- Available metadata includes:
- For TikTok:
id, title, description, channel, duration_seconds, view_count, like_count, comment_count, repost_count, save_count, uploader, uploader_url, channel_id, channel_url, webpage_url, timestamp, upload_date, thumbnails[], tags, categories, chapters, heatmap, availability, channel_follower_count
- For YouTube:
<span>id</span>, <span>title</span>, <span>description</span>, <span>channel</span>, <span>duration\_seconds</span>, <span>extractor</span>, <span>view\_count</span>, <span>like\_count</span>
WhisperLargeV3Ct2 is ideal for subtitles, podcasts, interviews, meetings, content indexing, speaker analysis, and social-media transcription pipelines where structured timing and metadata matter.