🎤 Audio Transcriber

🚀 Convert speech to text in seconds. Upload audio files and get accurate transcriptions. Supports multiple languages. No coding, no transcription accounts required.

Pull structured records from Audio Transcriber — clean fields ready as CSV, JSON, JSONL, Excel, or XML for downstream pipelines.

Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

parseforge/audio-transcriber on Apify. Call: ApifyClient("TOKEN").actor("parseforge/audio-transcriber").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. Key inputs: audioFileUrl (array, default ["https://upload.wikimedia.org/wikipedia/commons/e/e9/Mia_Lo), language (string, default "en"). Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parseforge~audio-transcriber (Bearer TOKEN). Get token: https://console.apify.com/account/integrations

Convert audio recordings to clean, structured text without juggling transcription tools or paying per-minute fees. The Actor accepts one or more audio file URLs (MP3, WAV, AIFF, AAC, OGG, FLAC, M4A and similar), runs each through an AI transcription pipeline, and returns the full transcript in your dataset. Built for podcasters, journalists, researchers, meeting teams, and any workflow that turns spoken audio into searchable text.

The output is a structured record per file: a back-reference to the input URL, the full transcription, a timestamp, and an error field if something fails. Hand the dataset off to your editor, summarizer, or downstream pipeline. Every run is processed live, so there is no upload cap or vendor lock-in.

👥 Built for	🎯 Primary use cases
Podcasters and creators	Generate episode transcripts and show notes
Journalists and researchers	Convert recorded interviews into searchable text
Meeting and operations teams	Auto-transcribe Zoom and Teams recordings
Content marketing	Repurpose webinars into blog posts and shorts
Accessibility teams	Produce captions and transcripts for compliance
Localization workflows	Get base text ready for translation pipelines

📋 What the Audio Transcriber does

• 🎧 Audio input. Accepts one or more audio file URLs in common formats (MP3, WAV, AIFF, AAC, OGG, FLAC, M4A).
• 🌐 Language hint. Pass an ISO 639-1 language code (e.g. en, es, fr, pt) to bias the model toward the right phonetics and vocabulary.
• 📝 Full transcription. Returns the complete text of each audio file as a single string per record.
• 🆔 Back-reference. Every record includes the original audio URL so you can rejoin transcripts to source files.
• ⏱️ Timestamp. Every record carries a timestamp field with the time the transcript was produced.
• ❗ Per-file error reporting. If a file fails (corrupt, unsupported, unreadable URL) the error appears on its own record without breaking the run.

The actor processes uploads in the order you provide them. Records stream into the dataset as transcripts complete, so you can start consuming results before the run is fully finished. Manual transcription typically takes 4-6 hours per hour of audio; this Actor returns the same text in minutes.

💡 Why it matters: spoken audio is everywhere (podcasts, interviews, meetings) but most data tooling is text-first. A reliable speech-to-text step unlocks search, summarization, translation, and analytics workflows that would otherwise be impossible.

📊 Data fields

Each record includes: audioReference, timestamp, transcription. All 3 field names come from a real production run, so what you see here is what lands in your dataset.

⚠️ Good to Know: the audio URL must be publicly reachable. If your file lives in a private bucket, generate a signed URL valid for the run's duration before passing it in.

🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the Audio Transcriber page on the Apify Store.
3. 🎯 Add your audio. Paste one or more audio URLs into audioFileUrl and (optionally) set language.
4. 🚀 Run it. Click Start and let the Actor transcribe each file.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to first transcript: 3-5 minutes for a short clip.

🔗 Recommended Actors

• 🎬 YouTube AI Transcriber - Transcribe YouTube videos via URL with full metadata
• 🖼️ Auto Video Thumbnail Generator - Auto-generate thumbnails from video uploads
• 📰 Article Extractor - Extract clean article text from any URL
• 📄 PDF to JSON Parser - Convert PDFs into structured JSON
• 🔍 RAG Web Browser - Fetch clean text for AI retrieval pipelines

💡 Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.

⚠️ Disclaimer. This Actor is an independent tool. The scraper accesses only audio you supply by URL and is intended for legitimate research, productivity, and content workflows. Users are responsible for ensuring they hold the rights to transcribe the audio they submit and for compliance with copyright, privacy, and consent laws in their jurisdiction.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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