Recognize Speech in a Video and Convert It to Text
Recognize Speech in a Video and Convert It to Text Typing up what was said in a recording is tedious, and manually pulling the audio out first is an extra chore. This node does both in one shot — hand it a single video and get back a clean text transcript of everything spoken in it, audio extraction handled for you. It runs on OpenAI’s Whisper Large V3, state-of-the-art open-source speech recognition that holds up on accents, background noise, and technical vocabulary. Language auto-detects by default, or force English, Korean, Japanese, or Chinese.
🏆 7.44 mean WER on the Open ASR Leaderboard, running at 145.51× real-time (RTFx)
What it does
This node takes one video file as input, pulls out its audio track, and returns a text transcript of everything spoken in it. The underlying model is OpenAI's Whisper Large V3 — one of the strongest open-source speech recognition models available, trained by OpenAI on 5 million hours of internet audio and known for handling accents, background noise, and technical vocabulary well. The studio exposes a curated language picker (Auto, English, Korean, Japanese, Chinese); the model itself supports 99 languages, so if you feed it audio in another language it will typically still work in Auto mode. This node is designed for the "one video → one transcript" workflow. If you have a list of clips and need timed transcripts per clip, use the sibling node Audio Understanding - Speech Recognition (Clips) instead.
Problem it solves
- One-shot video transcription – Feed a full video, get back the full spoken text — no manual audio extraction, no chunking
- Multilingual out of the box – Auto-detects the spoken language; explicit picker for the four most common languages in the studio's typical workflows
- Meeting / lecture / interview recordings – Turn long-form video recordings into readable text
- Podcast or video captioning – Get a full transcript for further editing into subtitles or show notes
- Content search & indexing – Make video content searchable via its transcript text
- Robust to real-world audio – Whisper Large V3 handles background noise, accents, and varied recording quality well
Input/Output
- Input: A single video file
- The node extracts the audio track from the video automatically
- Output: Plain-text transcript of everything spoken in the video
- Options:
- Spoken language (dropdown, default Auto)
- Auto — model detects the language from the audio itself (recommended for mixed or unknown-language content)
- English — force English
- Korean — force Korean
- Japanese — force Japanese
- Chinese — force Chinese
- Note: under the hood the model supports 99 languages; the studio's picker is scoped to the four most-used explicit choices
Accuracy & Speed
Model | OpenAI Whisper Large V3 — state-of-the-art open-source speech recognition |
Mean WER (Open ASR Leaderboard) | 7.44 — among the strongest open ASR models |
Real-Time Factor (RTFx) | 145.51 — much faster than real-time on capable hardware |
Improvement over Whisper V2 | 10 – 20% fewer errors across most languages |
Languages | 99 supported by the model; UI-exposed choices: Auto, English, Korean, Japanese, Chinese |
Long audio handling | Automatic — Whisper's 30-second receptive field is handled behind the scenes via chunked or sequential long-form inference |
Model size | 1.55B parameters |
How the Video variant compares
Speech Recognition (Video) | Speech Recognition (Clips) | |
Input | A single video file | A list of video clips |
Output | One plain-text transcript | A timed transcript per clip |
Best for | One video → one transcript | Per-scene / per-highlight captioning, subtitle alignment |
Underlying model | Whisper Large V3 | Whisper Large V3 |
Both run inside CNAPS Studio — for batch clip lists with per-clip timestamps use the sibling Audio Understanding - Speech Recognition (Clips) node, or compare them side-by-side.
Model Source
- Hugging Face
- Paper
- License: apache-2.0
Compliance & Provenance
Provider | OpenAI (open-source) |
Provider type | Specialized |
License | Apache 2.0 |
EU AI Act risk class | Minimal Risk |
Art. 50 transparency | Not applicable |
Region availability | Available globally |
Training data summary |
For more on how we classify models and mark outputs, see our AI Policy.