You can turn a saved lecture recording into study notes without uploading it to a transcription service. OGAD (Off Grid AI Desktop) uses a local speech model to extract the words, then a local chat model to organize them. Download both models first, attach the audio, and check the transcript before asking for notes.
| Download OGAD | Current desktop releases |
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The useful result is a set of notes you can check against the lecture. A clean summary is not enough if a missed word changes a definition or a formula. Keep the recording, transcript, and generated notes as separate references.
This guide uses a saved audio file. It does not require live meeting capture or automatic recording of your classes.
What do you need before you start?
Use OGAD on a supported Mac or Windows computer, a downloaded transcription model, and a downloaded text model. You also need the lecture saved as an audio file. Complete the app, model, and runtime downloads before disconnecting from the internet.
The desktop download page provides the current stable builds for Apple Silicon Macs and Windows x64. The attachment workflow below is available in desktop release 0.0.49 and later.
Prepare these items:
- The lecture audio stored on your computer, rather than only available through a streaming link.
- A local speech model that supports the lecture’s language.
- A local chat model that can understand that language and handle the text you give it.
- Enough free storage and memory for the selected models.
The two models have different jobs. The speech model converts audio to text. The chat model turns that text into notes. Selecting a local model for only one stage does not make the other stage local.
Which lecture files can you attach?
Use an audio file such as MP3, WAV, M4A, AAC, OGG, Opus, FLAC, or AIFF. OGAD routes these audio formats to transcription when you attach them in chat. A usable recording still needs clear speech and a file that the audio decoder can read.
If your lecture is saved as MP4 or another video format, export its audio to an audio file first. The ordinary video attachment path samples visual frames. It is not the same as transcribing the full soundtrack, so attaching a lecture video is not a substitute for the audio steps here.
Give the recording a useful name, such as biology-lecture-04-cell-division.m4a. The attachment name helps you identify which source a chat used later.
How do you create the transcript locally?
Select a local transcription model, set the spoken language, and attach the audio through the chat’s Attach files control. Wait for processing to finish. Open the attachment preview to inspect the extracted transcript before asking the chat model to summarize it.
1. Select the speech model
Download a multilingual transcription model such as Whisper Base from Models. Open model settings, select Transcription, and choose it under Current model.
Set Spoken language to the lecture’s language. Use Auto-detect if you do not know it. English-only models are suitable only for English speech.
2. Select a local text model
Choose a downloaded text model in Models for the notes. Keep the active transcription and text models local. A remote model needs its connection and processes that stage elsewhere.
Start with a model that fits your computer’s available memory. There is no requirement to choose the largest model before trying a short lecture section.
3. Attach the recording
Open a chat, select the + composer menu, then Attach files. Choose the audio file.
The attachment shows Processing… while the app extracts text. Wait until it has a transcript before sending your notes request.
4. Read the full extracted text
Click the attachment’s text preview to expand it. The side panel shows the extracted transcript, rather than only the small preview on the attachment card.
Check a passage from the start, middle, and end of the recording. Pay special attention to subject-specific terms, numbers, and words that change a claim, such as “not” or “only.”
If the transcript is wrong, review the original audio. You can copy the extracted text into a text editor, correct it, and attach the corrected text as a new source. Label it clearly and remove the incorrect attachment from the new request so the model has one version to use.
5. Request a structured set of notes
With the checked source attached, send a request such as:
Use only the attached lecture transcript. Create study notes with topic headings, key definitions, and the examples used by the lecturer. Keep technical terms and numbers unchanged. Mark unclear passages as “Needs checking”. Do not fill gaps with outside facts. End with a short list of questions the lecture leaves unanswered.
This tells the model what to produce and where its evidence should come from. Still check the answer: a prompt is not a guarantee that every statement will be supported.
How do you check whether the notes are faithful to the lecture?
Compare the notes with both the transcript and the recording. The transcript lets you find the relevant wording quickly. The recording lets you check whether the speech model heard it correctly. A generated summary can repeat a transcription error or add an unsupported explanation.
Use this review table:
| Item in the notes | What to verify |
|---|---|
| A definition | Does the lecturer define the term this way? |
| A number, date, or formula | Does it match the audio and any supplied course material? |
| A worked example | Are the steps present, and is their order correct? |
| A conclusion | Did the lecturer state it, or did the model infer it? |
| A missing topic | Is it absent from the transcript, omitted by the summary, or outside the material supplied? |
For difficult passages, ask:
For each claim in these notes, quote a short supporting passage from the attached transcript. If you cannot find one, label the claim “Not supported by this transcript”. Do not invent timestamps or page numbers.
Check the quoted passages too. This attachment workflow supplies text to the model; it does not automatically create verified time-coded citations.
What if the lecture is too long for one request?
Work through it in sections. A complete transcript in the preview does not mean every chat model can use the whole lecture in one prompt. The model’s context limit also has to accommodate your instructions, conversation history, and its answer.
Split the corrected transcript at topic boundaries in a text editor. Save clearly named sections and give each one a separate chat request. Ask for the same note format each time.
Once the section notes are checked, combine them with a request such as:
Combine these section notes into one revision outline. Keep their source section labels. Remove repeated points without removing exceptions or conditions. List any conflicting statements for me to check.
Do not ask the model to invent the missing middle of a lecture because the opening and closing sections seem familiar.
Can you make practice questions from the notes?
Yes. Give the local chat model the checked notes and ask for questions that can be answered from that material. Separate the questions from the answer key so you can try them before reading the answers.
For example:
Create eight short-answer questions from the attached notes. Include questions that ask me to explain a concept and apply an example. Put the answer key after all questions. For each answer, name the note heading that supports it. Do not add topics absent from the notes.
For a topic you find difficult:
Ask me one question at a time about this section. Wait for my answer. Compare it with the supplied notes, explain any missing point, then ask the next question.
Use these as practice prompts. They do not predict what will appear in an exam.
Should you use a project for a whole course?
A project is useful when you want to ask questions across several lectures and course documents. A chat attachment supplies material for the current conversation. Project documents provide a separate knowledge base that the app can search for relevant passages, with sources attached to grounded answers.
In Projects, open the course project and use Add files to add the corrected transcripts and other course documents. Select that project when you chat. For offline use, finish setup for the local models used by the project before disconnecting.
Ask a focused question such as, “How does lecture 4’s definition relate to the example in lecture 6?” Open the returned sources and check the supporting text. A citation is useful for finding evidence; it does not make an incorrect transcript correct.
Keep plain notes and the original audio too. Searching a project for a few passages is a different task from reading every line of every lecture.
Can the whole process work without internet?
Yes, when the audio is already on your computer and the transcription and text models are downloaded and selected locally. Model or runtime downloads need a connection first. Remote models and connected web tools have their own network requirements.
Try one short lecture section while disconnected. Expand its transcript, check the important terms, and produce one page of notes before processing the rest of the course.