GPT Transcribe
AI speech to text in 100+ languages, on Whisper
GPT Transcribe is an online AI speech to text workspace that converts audio and video recordings into searchable, timestamped transcripts. Every job runs on OpenAI Whisper, a model trained on hundreds of thousands of hours of multilingual speech, so regional accents, industry jargon and background noise hold up far better than they do in phone dictation tools. Upload an MP3 or MP4, record live in the browser, or paste a media link; GPT Transcribe detects the language from 100+ options, labels each speaker, and drops the transcript into an editor where you can search, correct a misheard name, and export in the format your next step needs. Every account starts with free transcription minutes.
Features
Three ways in: upload a file, record live in the page, or paste a media URL. Audio and video in one console — MP3, WAV, M4A, FLAC, OGG, MP4, MOV and WebM, up to 1GB per upload. 100+ languages with automatic detection. Speaker diarization that splits interviews and panels by voice. An in-browser editor with search and timestamp-safe corrections. Six export formats: TXT, SRT, VTT, JSON, PDF and DOCX. AI Summary, AI Analytics, transcript chat and translation into 100+ languages on Pro and Max plans.
Use Cases
Journalists turn recorded interviews into quotable, speaker-labelled text. Video creators export SRT captions straight into YouTube or an editing timeline. Podcasters produce show notes and searchable episode archives. Product and operations teams keep meetings and stand-ups searchable months later. Students and researchers transcribe lectures, seminars and field recordings. Developers pipe JSON transcripts with timestamps into their own automation.
Comments
We built GPT Transcribe because every transcription tool we tried stopped at a wall of unpunctuated text. The work that actually matters happens after the transcript appears: checking a misheard name, finding the quote you remember, and getting it out as SRT or DOCX without a round trip through another converter. So we put intake, language detection, speaker labels, the editor and six export formats on one screen, running on OpenAI Whisper. Happy to answer questions about accuracy on noisy audio or the export pipeline.
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Comments
We built GPT Transcribe because every transcription tool we tried stopped at a wall of unpunctuated text. The work that actually matters happens after the transcript appears: checking a misheard name, finding the quote you remember, and getting it out as SRT or DOCX without a round trip through another converter. So we put intake, language detection, speaker labels, the editor and six export formats on one screen, running on OpenAI Whisper. Happy to answer questions about accuracy on noisy audio or the export pipeline.
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