Hebrew & Arabic Audio Transcription + RTL Subtitles (Whisper)

Turn Hebrew and Arabic audio or video into accurate text, timestamped segments and SRT / WebVTT subtitles that display correctly right-to-left. Hebrew is transcribed with ivrit.ai's Hebrew-tuned Whisper large-v3-turbo, which is much more accurate on Hebrew than generic Whisper; Arabic and 90+ other languages use Whisper large-v3-turbo.

Everything runs inside the Actor: no OpenAI / Deepgram API key, no third-party upload, no scraping. You provide files you own or are allowed to process; results go only to your own Apify storage.

What you get

• 📝 Transcript text (one line per spoken segment)
• ⏱️ Timestamped segments and optional word-level timestamps
• 🎬 SRT and VTT subtitles with broadcast-style line wrapping (42 chars × 2 lines by default) and the RTL punctuation fix (periods, question marks and numbers stay on the correct side in VLC, YouTube, browsers and editors)
• 💾 .srt / .vtt files saved to the key-value store for direct download
• 🌍 Auto language detection, or force Hebrew / Arabic / English / Russian / French / Spanish / Amharic / Yiddish
• 🔁 Optional translation to English

Typical uses

• Subtitles for Hebrew/Arabic courses, webinars, podcasts, marketing videos and Reels you produced
• Meeting and interview transcripts for your team (with your participants' consent)
• Feeding Hebrew/Arabic audio into RAG, search and AI agents (LangChain, LlamaIndex, n8n, Make, MCP)

Input example

{
  "mediaUrls": [{ "url": "https://example.com/my-webinar.mp4" }],
  "language": "he",
  "outputFormats": ["text", "srt"],
  "vocabularyHint": "Apify, ivrit.ai, תל אביב"
}

Upload files in Apify Console (they go to your own key-value store) or pass any direct https:// link: S3, Google Cloud Storage, Dropbox direct links, your own server. Supported: MP3, WAV, M4A, AAC, OGG, OPUS, FLAC, MP4, MOV, MKV, WEBM and anything else ffmpeg can read. YouTube or social-media page links are not supported.

Output example

Real output on a 30-second clip of the Hebrew Spoken Wikipedia article "שחמט" (CC BY-SA 3.0):

{
  "fileName": "he_chess_30s.ogg",
  "status": "ok",
  "language": "he",
  "direction": "rtl",
  "durationSeconds": 30.0,
  "billedMinutes": 1,
  "model": "ivrit-ai/whisper-large-v3-turbo-ct2",
  "text": "שחמט הוא משחק לוח אסטרטגי המיועד לשני שחקנים.\nזהו אחד מהמשחקים השכיחים והמורכבים ביותר הקיימים בתרבות האנושית.\n…",
  "segments": [{ "start": 0.28, "end": 3.32, "text": "שחמט הוא משחק לוח אסטרטגי המיועד לשני שחקנים." }],
  "srtKey": "subtitles-0001-he_chess_30s.srt"
}

SRT excerpt:

1
00:00:00,280 --> 00:00:03,320
שחמט הוא משחק לוח אסטרטגי
המיועד לשני שחקנים.

Pricing

$0.08 / minute, $4.80 per hour of audio (billed per started minute, with a 1-second grace) — Pay per event, you only pay for files transcribed successfully. Failed downloads, unreadable files and silent files are free. A 45-minute Hebrew lecture costs $3.60. Set Maximum cost per run and the Actor will stop (or truncate the last file) before exceeding it.

Tips for best accuracy

• Set language explicitly when you know it (faster, avoids detection mistakes on short clips).
• Put names and jargon in vocabularyHint.
• Use 8 GB memory (default). More memory = more CPU = faster runs, same price per minute.
• Keep skipSilence on: it trims long silences and prevents Whisper from "hallucinating" text in silence.

Limitations

• No speaker diarization (who said what) in this version.
• Very noisy audio, music or heavy overlapping speech reduce accuracy, as with any ASR.
• Speed (measured): about real time at 8 GB memory (a 3-minute file took ~3.5 minutes plus ~1 minute start-up); 16–32 GB memory gives more CPU cores and proportionally faster runs.

Privacy & legal

• Process only media you own or have the rights and, where required, the participants' consent to transcribe.
• Files are processed in your own run and are not kept by the developer. Logs contain no URLs, file names or transcript text.
• Models: ivrit-ai/whisper-large-v3-turbo-ct2 (Apache-2.0), Whisper large-v3-turbo (MIT) via faster-whisper (MIT). Media decoding by FFmpeg.

Related Actors

• Hebrew & Arabic PDF to Markdown – RTL-correct document conversion with OCR.
• RTL Subtitle Fixer & Converter – fix Hebrew/Arabic punctuation, encoding and timing of existing SRT/VTT files.