Export your WhatsApp chat with media, transcribe all voice notes, merge them into the message timeline, then extract decisions and action items.
Oct 18, 20258 min read
If your conversation uses voice notes, a normal WhatsApp summary is often wrong because it only sees the text. The correct workflow is:
Export the chat as a .zip with media.
Transcribe every voice note.
Merge transcripts back into the chat timeline.
Summarize the full conversation with decisions and action items.
This is exactly the gap ThreadRecap is built to solve: its voice-to-text tool can transcribe WhatsApp voice notes and analyze text + audio together.
What WhatsApp voice notes actually are
WhatsApp voice notes are typically saved as `.opus` files (sometimes `.m4a`) inside the exported `.zip`.
If you export without media, you get the text log but the voice notes are missing.
If you export with media, the .zip includes audio files and the chat text file references them.
Practical takeaway: no media, no audio transcription.
Step 1: Export the chat with media
iPhone
Open the chat.
Tap the contact or group name.
Scroll to Export Chat.
Choose Attach Media.
Save or share the `.zip`.
Android
Open the chat.
Tap the menu (three dots).
Tap More.
Tap Export chat.
Choose Include media.
Save or share the `.zip`.
Tip: if your export becomes too large, start with a smaller timeframe (recent month, recent project, recent incident) instead of uploading years of history.
Step 2: Verify the export contains voice notes
Inside the `.zip`, you should see something like:
A chat text file (often `_chat.txt` or `WhatsApp Chat - ... .txt`).
Multiple `.opus` or `.m4a` audio files (voice notes).
If you do not see `.opus` or `.m4a` files, you exported without media or WhatsApp did not include them.
Step 3: Bulk transcription strategy (the only one that scales)
Transcribing voice notes one by one is a waste of time. A scalable tool should:
Parse the chat log and detect every voice note reference.
Upload audio files individually (not the whole zip blob).
Transcribe using a speech-to-text model (Whisper-class models are common).
Return timestamps and text per clip.
Merge transcripts into the correct place in the conversation timeline.
That last step is the difference between "audio transcripts" and "a usable recap."
Step 4: Merge transcripts into the timeline
When merged correctly, each voice note becomes a normal message in the timeline, for example:
Sender: Alex.
Type: audio.
Transcript: "Ok, we will ship Friday. John owns the landing page. I will handle billing."
Timestamp: aligned with the original audio message.
Now your analysis can correctly extract:
Decisions: ship Friday.
Owners: John for landing page.
Action items: billing tasks.
Open questions: anything unresolved in the transcript.
Without timeline merge, the AI often misses commitments that were only spoken.
Step 5: Turn transcripts into real outputs
If your goal is work outcomes, the best output formats are:
Meeting recap
Context and purpose.
Agenda topics in order.
Decisions made.
Action items (owner, deadline if mentioned).
Open questions.
Suggested follow ups.
Action items only
Task list.
Owner per task.
Deadline or "no deadline mentioned."
Blockers.
Conflict resolution
Root cause.
Each side's perspective.
Misunderstandings.
Resolution status.
Next steps.
If you are building for conversion, make these a one click goal selection before analysis.
Accuracy tips (simple, high impact)
Transcription quality depends on audio quality. Users can improve results by:
Recording closer to the mic.
Avoiding speaker overlap.
Reducing background noise.
Keeping voice notes shorter and more focused.
If the transcript looks off, it is usually a noisy clip, multiple speakers, or a very low volume recording.
Common problems and fixes
My export is missing voice notes
You exported without media. Re-export and choose include or attach media.
My zip is too big to upload
Start with a smaller timeframe. If you only need "what happened this week," do not upload 3 years of media.
The tool transcribed audio but the recap is still generic
That usually means transcripts were not merged into the conversation context. Transcripts must be inserted into the same timeline as text messages before analysis.
Group chats are noisy
Focus analysis on the key participants and collapse everyone else into a generic bucket. This reduces noise and cost while keeping the signal.
Privacy basics for voice notes
Voice notes can include identity cues, names, locations, and confidential details. A serious tool should:
Preview what will be processed before upload.
Upload only what is required for the chosen analysis.
Delete server-side content by default after analysis unless the user explicitly saves it.
If a tool cannot clearly explain this, do not upload sensitive exports.
FAQ
Can I transcribe WhatsApp voice notes to text for free?
Some tools do, but "free" usually means strict limits or unclear data handling. If privacy and reliability matter, treat free tools as higher risk unless they are transparent.
What file format are WhatsApp voice messages?
Commonly `.opus` (sometimes `.m4a`) inside the exported `.zip`.
Do I need media export for transcription?
Yes. No media means no audio files to transcribe.
What is the best end result to aim for?
A searchable timeline where voice notes are merged back into the conversation, then a structured output like decisions plus action items.
Export your WhatsApp chat with media, upload the .zip, transcribe voice notes in bulk, and generate a structured recap with decisions and action items in minutes.
Ready to analyze your WhatsApp chat?
Upload your export and get summaries, insights, and voice note transcriptions in minutes.
