Start AI Meeting Notes by Choosing the Recording Source
An AI meeting notes tool is not one feature; it is a workflow: recording → transcript → summary → action items → archive / sharing. The final AI summary is not the main quality driver. Audio source, participant consent, language mix, and whether the file can go to the cloud matter more.
For personal Chinese meetings, start with the free iPhone + Gemini Notebook (formerly NotebookLM) route. For English team calls, compare Otter and Fireflies. For sensitive content or product integration, use Whisper or the OpenAI API route.
Four common recording sources:
| Source | Best for |
|---|---|
| Phone Voice Memos | Personal use, in-person meetings, low barrier |
| Built-in online meeting recording (Zoom / Meet / Teams) | Remote meetings with recording permission |
| Meeting bot (Otter / Fireflies) | Marketing / sales teams, managing a meeting library |
| External hardware recorder (such as Plaud) | Mobile scenarios, many venues, clearer voice capture |
“Which tool records the meeting?” determines everything that comes later: recognition accuracy, privacy boundary, and whether the content can be searched.
Privacy and Consent: Handle It Before Recording
- Tell all participants: state before the meeting that it will be recorded and explain the purpose.
- Follow company policy: many companies have rules for recording / AI processing.
- Data retention: if uploaded to a third-party cloud service, check how long records stay and whether they are used for training.
- Legal region: for cross-border meetings, follow the strictest applicable region.
This step is not inside tool selection, but it is worth understanding in advance to protect yourself.
A simple opening line works: “This meeting will be recorded only for post-meeting transcript and summary. The result will be stored in the agreed folder. If anyone objects, please say so now.” For company or client meetings, follow internal policy as well.
Personal Free Workflow Recommendation: iPhone + Gemini Notebook
| Step | Tool | Key point |
|---|---|---|
| Record | iPhone Voice Memos | Within 2 meters on the table, clear speech |
| Import | Gemini Notebook | Drag the audio file in; transcript is generated automatically |
| Summarize | Gemini Notebook chat | ”Please organize key points + action items” is enough |
| Advanced analysis | Large model (Claude / ChatGPT) | Send the transcript to a large model for summary, topic grouping, and meeting conclusions |
| Subtitles | CapCut | Video content and mixed Taiwanese Hokkien subtitle scenarios |
Why Gemini Notebook:
- Free, with reasonable quota (Standard: 50 chats / 3 audio generations per day).
- Stable Chinese transcript performance.
- Output can include citations, making proofreading easier by locating segments.
Notes:
- Upload limit is 200 MB / 500,000 words (Gemini Notebook Standard).
- Very poor audio quality may fail import.
- It is a post-meeting organization tool. For live meeting bot scenarios, use other tools.
The full SOP is in Free AI Meeting Notes Workflow, and transcript details are in Gemini Notebook Transcript Guide. If all meeting notes later live in Notion, also check whether Notion AI Meeting Notes is worth upgrading.
What Meetings Otter / Fireflies Fit
| Tool | Strength |
|---|---|
| Otter | English real-time transcription, speaker diarization, meeting search |
| Fireflies | Team meeting library, cross-meeting search, CRM integration, 800 mins free storage |
Good for:
- Sales / customer success teams with many online meetings every week.
- Workflows already comfortable with meeting bots joining Zoom / Meet automatically.
- Scenarios where meeting outcomes need to go into CRM / Slack.
Not good for:
- Chinese-first individuals with limited budget.
- Scenarios where a third-party bot should not join meetings.
Who Should Use Whisper / OpenAI API
| Form | Key point |
|---|---|
| OpenAI Speech-to-Text API | whisper-1, gpt-4o-mini-transcribe, gpt-4o-transcribe, gpt-4o-transcribe-diarize; 25 MB upload limit; usage-based pricing (Whisper $0.006/min, etc.) |
| Whisper open source | Run locally if hardware is sufficient; audio does not leave the machine |
Good for:
- Developers building transcription into their own systems.
- Highly sensitive content where recordings should not leave the machine.
- Custom language, terminology, and post-processing workflows.
Not good for:
- Non-engineers who want a ready-to-use product without technical resources.
The Reality of Chinese, Taiwanese Hokkien, and Mixed Chinese-English
- Pure Mandarin + clear audio: most tools are acceptable.
- Mixed Chinese-English: frequent pronunciation switching causes unstable recognition; clear audio and stable speech help.
- Taiwanese Hokkien: CapCut is usable in practice but still needs human correction; most English-centered tools are not suitable.
- Multilingual meetings: first generate transcripts with a multilingual tool, then use a large model to merge segments.
How to Choose the First Tool Stack
| Scenario | Starting point |
|---|---|
| Personal / budget 0 / Chinese-first | iPhone + Gemini Notebook |
| Personal / video content creation | iPhone + Gemini Notebook + CapCut |
| Team / many online meetings / English | Otter or Fireflies |
| Developer / highly sensitive | Whisper open source locally or OpenAI API |
| Highly sensitive + existing OpenClaw / self-hosted stack | API transcription + own retention |
Tool Selection Table: Start with Meeting Type
| Meeting type | First choice | Limit to remember |
|---|---|---|
| Personal Chinese meetings, zero budget | iPhone + Gemini Notebook | No live transcript or automatic speaker labels |
| English online meetings needing live captions | Otter | Chinese is not its strength |
| Team meeting library with CRM / Slack integration | Fireflies | Can be overkill for one person |
| Sensitive content that should not go to cloud | Local Whisper | You manage setup and post-processing |
| Product transcription feature | OpenAI Speech-to-Text API | Cost, 25 MB upload limit, and governance need planning |
For pricing, language support, and detailed limits, read AI Meeting Notes Tools Comparison.
Conclusion
The bottleneck of meeting notes is the recording source, language, privacy, and downstream collaboration. AI summary quality actually comes after those four. Clarify these first, then choose the tool. It saves a lot of backtracking. The lowest-cost personal entry point is iPhone + Gemini Notebook, and most needs can already be covered by that route.
Penchan’s Take
The main flow: iPhone Voice Memos → Gemini Notebook Studio transcript → send the transcript to Claude / ChatGPT for final analysis. Fully free, with relatively simple governance across Apple + Google.
Gemini Notebook’s Chinese transcript quality makes post-meeting organization smooth. It is not a live bot, which fits the habit of “record the meeting first, organize later.” For mixed Taiwanese Hokkien scenarios, Penchan uses CapCut audio-to-text in practice (real Q19 experience), and the accuracy is good enough before sending it into a large model for polishing.