Transcription
X (Twitter)
Tools
Spaces on X (formerly Twitter) are hard to catch up on once you miss them. Even when the archive is still available, sitting through an hour of audio a second time is rarely practical. With a transcript you can read only the parts you need.
A transcript is useful in a number of situations:
- Catching up on a Space you missed
- Searching back for a particular remark
- Quoting what was said accurately
- Writing up a Space you hosted as a post or an article
- Keeping minutes or a record of the discussion
This article explains how to turn a published Space recording into text. Everything runs in your browser. You do not need an account, and there is nothing to install or pay for.
The process has two stages: saving the recording as an audio file, and transcribing that file. Each stage uses a different tool, but both run in the browser.
Two ways to transcribe a Space
There are two general approaches. You can generate captions live while the Space is running, or you can transcribe the recorded archive after it ends.
Live captions | Transcribing the archive | |
|---|---|---|
When it works | Only during the broadcast | Any time after the Space ends |
What it covers | The Space you are listening to right now | Any Space with a published archive |
Accuracy | Lower, because it runs in real time | Higher, because the full audio is processed |
Keeping the result | Usually not saved | Saved as a text or subtitle file |
Separating speakers | Difficult | Speakers can be split apart |
This article covers the second approach. It suits you if you want to catch up on a Space you missed, or turn the content into notes or an article.
What you need
- The URL of a Space whose archive is public
- A PC or a smartphone — a browser is enough
- Free storage for the transcription model (about 40 MB at minimum, up to 1.6 GB for the largest model)
- Spare memory for the run itself (around 300 MB on the smallest model, over 3 GB on the largest)
No dedicated app, and no development environment such as Python, is required.
Step 1: Download the Space recording
First, save the recording as an audio file using the tool below.
Download published recording archives of X (formerly Twitter) Spaces as M4A. Save Spaces you missed to your PC (Windows/Mac) or phone (iOS/Android) and listen offline. Just paste a URL — no account, completely free.
- Copy the URL of the Space you want to save. A direct link to the Space works, and so does the URL of a post the Space is attached to.
- Paste it into the input field and press Execute. The download is processed on the server.
- When processing finishes, the Download button becomes available. The recording is saved as an M4A audio file.
A more detailed walkthrough of the download step, including a command-line method, is covered in a separate article.
Until June 2022, Twitter Spaces recording archives were automatically deleted after one month. However, this policy was later changed to allow unlimited storage, meaning recordings stay available for as long as the host keeps them public.
Step 2: Transcribe the downloaded audio
Next, convert the saved audio into text using the tool below.
Transcribe audio and video files entirely in your browser. No account and no upload — your audio never leaves your device. Free with no time or usage limits. Speaker diarization and SRT subtitle export powered by Whisper.
The M4A file from step 1 can be loaded directly. There is no need to convert it to MP3 first.
- Open the page and select the audio file. Drag and drop also works.
- Choose the model and the spoken language. Pick the language explicitly rather than leaving it on auto-detect.
- Start the run. Progress is shown, and the transcript appears on screen when it finishes.
The model is downloaded on the first run. After that the browser reuses the stored copy, so later runs start faster.
Choosing a model
Six models are available. Larger models are more accurate, but they take longer to download and to run.
Model | Download | Memory while running | Speed | WebGPU |
|---|---|---|---|---|
Whisper Tiny | ~40 MB | ~300 MB | Fast | No |
Whisper Base | ~200 MB | ~600 MB | Moderate | No |
Whisper Small | ~600 MB | ~1.5 GB | Slow | No |
Whisper Medium | ~900 MB | ~2.2 GB | GPU recommended | Yes |
Whisper Large v3 Turbo | ~1.2 GB | ~2.6 GB | GPU recommended | Yes |
Whisper Large v3 | ~1.6 GB | ~3.5 GB | Slowest | Yes |
For audio as long as a typical Space, start with Base or Small. If your browser supports WebGPU, Large v3 Turbo gives the best balance of accuracy and speed. The page shows whether WebGPU is available on your device.
Separating speakers
A Space usually has several people talking. A transcript that does not mark who said what is difficult to read back.
With speaker diarization enabled, each speaker's lines are colour-coded. The number of speakers can be detected automatically, or set between two and six. If you already know how many people took part, setting the number gives more stable results.
Speaker labels can be edited afterwards. Replacing "Speaker A" with the actual name makes the transcript far easier to read, and the change carries over to the exported file.
Exporting text and subtitles
Once the transcript is ready, you can take it out in three ways.
Export | What you get | Use it for |
|---|---|---|
Copy | The transcript on your clipboard | Pasting straight into a note or an editor |
TXT | A plain text file without timestamps | Reading the content, writing it up as an article |
SRT | A subtitle file with timecodes | Loading into video editing software, locating a quote by time |
If speaker diarization was enabled, every export keeps the speaker labels.
Improving accuracy
- Set the language explicitly. Auto-detect can pick the wrong language on short utterances or on speech with many borrowed English words.
- Move up a model size. Try a few minutes with a small model first, and switch to a larger one only if the result is not good enough. Starting with the largest model means a long download before you learn anything.
- Check the source audio. Clipping, background noise and overlapping speech reduce accuracy on any model. That cannot be recovered on the transcription side.
Frequently asked questions
Can I transcribe a Space that was not recorded?
No. Only Spaces with a published archive can be used. If the host chose not to keep an archive, no recording exists to work from.
Can I transcribe a Space live, while it is running?
Not with this method. Wait until the Space ends and the archive becomes available.
How long a Space can this handle?
There is no limit on duration. The limit is on file size: 500 MB per file, or 100 MB on a smartphone. An M4A recording of a Space lasting several hours generally stays within that.
Can I do all of this on a phone?
Yes. Both tools run in the browser, so nothing needs to be installed. Downloading the model and running the transcription do take a while, so a PC is more comfortable for long recordings.
Is my audio uploaded anywhere?
Transcription runs in the browser, so the audio file is not sent to a server. The download step in stage 1 does fetch the Space through a server.
Is it acceptable to transcribe someone else's Space?
Transcribing it to understand the content yourself is generally treated as personal use. Publishing or distributing the transcript without permission is a different matter and may conflict with the speakers' rights or with the X terms of service. Ask the speakers first if you intend to publish it.
Summary
Split into two stages — downloading the recording and transcribing it — the whole process runs in a browser, with no account and no cost.
- Save the recording: paste the Space URL and receive an M4A file
- Transcribe: load the M4A directly and enable speaker diarization
- Export: TXT to read it back, SRT to use it with video
Because the audio never leaves your device, this also works when you would rather not hand the content to an external service.
Download published recording archives of X (formerly Twitter) Spaces as M4A. Save Spaces you missed to your PC (Windows/Mac) or phone (iOS/Android) and listen offline. Just paste a URL — no account, completely free.
Transcribe audio and video files entirely in your browser. No account and no upload — your audio never leaves your device. Free with no time or usage limits. Speaker diarization and SRT subtitle export powered by Whisper.
If your machine has the capacity and you are comfortable with a command line, the same result can be produced with Python.
This article provides a comprehensive guide to converting audio files—including videos and meeting minutes—into text completely free of charge using Python.
Programing
Python
Hosting