Transcribe Audio to Text Online

Transcribing audio to text with VexaScribe is straightforward. Upload your audio file (MP3, WAV, M4A, or other formats) using drag-and-drop or the file browser. Our AI-powered transcription engine will automatically process the audio, detect spoken words, identify different speakers, and generate a timestamped transcript. The entire process typically takes just a few minutes. Once complete, you can review the transcript in our editor, make any corrections, and export it in your preferred format.

VexaScribe supports virtually all common audio and video formats. This includes MP3, WAV, M4A, FLAC, OGG, OPUS, AAC for audio files, and MP4, MOV, AVI, MKV, and WebM for video files (we extract the audio track automatically). If you have recordings from a smartphone, voice recorder, podcast software, or video conferencing tool, chances are the format will work. Files up to 5GB are supported.

Real accuracy on clean English audio is 92-97% (WER 3-8%), verified against the Open ASR Leaderboard — not the '99%' most services advertise. Multiple overlapping speakers, heavy accents, phone-quality audio, or background music drop it to 75-88%. Only professional human transcription reliably hits 99%+. Our stack (Whisper Large V3 Turbo + pyannote 4.0 community-1) is essentially equivalent to what TurboScribe, HappyScribe, and Otter run — the differentiation is honesty about the numbers, not the model.

Most audio files are transcribed in a fraction of their actual runtime. A typical 1-hour recording completes in about 5-10 minutes. Shorter files like 10-15 minute voice memos are usually ready in 1-2 minutes. The exact time depends on file size, audio complexity, and current server load. You can close the browser while processing—we'll keep your transcript ready for when you return.

Yes, VexaScribe supports transcription in 99 languages. This includes widely spoken languages like English, Spanish, French, German, Portuguese, Italian, Dutch, and Russian, as well as Chinese, Japanese, Korean, Arabic, Turkish, Hindi, and many others. The system can automatically detect the language being spoken, or you can specify it manually for best results. This makes VexaScribe useful for international teams, multilingual content, and global businesses.

Yes, VexaScribe includes automatic speaker detection (also called speaker diarization). When multiple people are speaking in a recording—such as in meetings, interviews, or podcasts—the system identifies and labels each speaker separately (Speaker 1, Speaker 2, etc.). This makes it much easier to follow conversations, attribute quotes correctly, and create professional transcripts. You can also rename speakers in the editor for clarity.

VexaScribe offers multiple export formats to fit your workflow. Choose plain text (TXT) for simple documents and quick sharing, Word format (DOCX) for documents you'll edit further or include in reports, or subtitle formats (SRT, VTT) for adding captions to videos. All export formats preserve timestamps and speaker labels when available. You can also copy the transcript directly to your clipboard for pasting into other applications.

Yes, VexaScribe can generate subtitle files from any audio or video file. After transcription, export your transcript as SRT (SubRip) or VTT (WebVTT) format — both are widely supported by YouTube, TikTok, LinkedIn, and most video editing software. Each subtitle segment includes precise timestamps synced to the original audio. Visit our subtitle generator page for more details.

Yes, data security is a priority. Your audio files are encrypted during upload and throughout processing. Transcripts are stored securely in your account, and you maintain full control over your data. You can delete files and transcripts at any time, and we never train our models on your audio without explicit consent. For sensitive recordings (legal depositions, medical, source-protected journalism) consider running Whisper locally instead — the audio never leaves your machine that way.

Yes. Paste the YouTube URL directly — we extract the audio and transcribe it, no download required. Works with public videos in 99 languages. This is the fastest workflow for citing YouTube content, summarizing lectures, or repurposing videos into blog posts. Private, unlisted, or age-restricted videos aren't supported — for those, download the audio locally first (yt-dlp, etc.) and upload the file.

Whisper Large V3 Turbo, released by OpenAI in late 2025, is the same encoder as whisper-large-v3 but with a smaller decoder — roughly 8× faster inference for equivalent transcription quality on English. Multilingual audio shows a small quality drop (1-3% WER increase). We run Turbo as the default because the speed advantage is significant and quality is essentially unchanged for most use cases. If you have specific low-resource languages, uploading and testing both is the honest recommendation.