How to Transcribe a Medical Lecture or Conference Talk

Recording a lecture is the easy half. Vocabulary is the half people worry about, and it is mostly the wrong worry: the speech model Kalima runs on is built for specialist domains, medicine among them, so clinical terminology, drug names and the usual abbreviations arrive as ordinary input rather than as a special case. You are not starting from zero, and you do not have to prepare anything to get a usable transcript.

What no model can know is the part that is local to you: your department's in-house abbreviations, a regional brand name, the speaker's surname, an internal study code. Closing that gap is what session context is for. It takes about two minutes, it is available on every plan, and it is optional.

This guide covers grand rounds, congress sessions, university lectures, CME and Fortbildung talks, and journal clubs. It is about teaching and conference material, not patient records. If you are evaluating transcription for anything that touches patient data, talk to us first so we can go through the requirements with you properly.

What the model already handles, and what it cannot

Healthcare is one of the domains the transcription engine is designed to serve, so the vocabulary a talk is actually made of is not the hard part:

• Drug names, generic and brand, including the long compound ones nobody spells the same way twice.
• Eponyms. Morbus Crohn, Ormond, Bechterew. They sound like surnames because they are surnames, and choosing the right one from context is precisely what a domain-aware model is good at.
• Abbreviations spoken as sound. NSTEMI, COPD, GFR, CRP.
• Latin and anatomical terms, where the ending carries the meaning.
• Language mixing. A German talk that switches into English terminology every second sentence comes back as one document, with each part labelled in the language it was spoken.

The shorter list is the one worth preparing for, because it is specific to you and could not be in any model:

• In-house abbreviations, ward names and the internal shorthand that means nothing outside your building.
• The speaker's surname, and the names of the people and studies they cite.
• Regional brand names, an internal protocol or study code.
• Anything that has to be spelled one exact way every time, because it gets pasted into a document afterwards.

Everything below is about that second list.

Context is optional, and it takes two minutes

Kalima calls this session context: a short briefing plus any terms you want pinned. It is available on every plan at no extra cost, and you can skip it.

Skipping it is not the same as sending nothing. When you configure no context of your own, Kalima still passes the model a small, truthful briefing built from what the app already knows: the capture setting, the session title, and the project the session sits in. A session you set up in four clicks is not a session running blind.

What you add on top does two different jobs, and the cheaper one is the one that pays:

• A description. Two or three sentences naming the field, the topic and the setting. This is the high-return half, because it positions the model in the right domain without you having to predict a single word: "Cardiology grand rounds on acute coronary syndromes, speaker Prof. Weber, audience questions at the end" is already enough to change how an ambiguous word gets resolved. The in-app quick description field takes up to 2,000 characters, far more than this needs.
• Key terms and names. The optional refinement, aimed at the local list above: ward abbreviations, the speaker's surname, an internal code, anything that must be spelled one exact way. Spell each one the way it should appear in the transcript. A term is a hard bias, so a short deliberate list beats a long defensive one padded with vocabulary the model already has.

If you also translate the session, you can supply preferred translations for individual terms so they come out consistently instead of being translated literally. That matters for terminology that has an established equivalent nobody would recognise from a literal rendering.

Do not type two hundred terms by hand

For a recurring series a proper glossary does pay off, and writing one by hand is the reason most never get built, so Kalima can draft it. Open Templates in the Studio sidebar and choose Build with AI. Describe what you record in two or three sentences, press Build the template, and a finished template opens in the editor, typically with 200 to 350 terms plus a briefing. Nothing is saved until you review it, so you name it, cut what does not belong, and save.

If you would rather use your own assistant, the same dialog gives you a ready-made instruction to paste into ChatGPT or anything else, and Kalima reads the answer back even when it arrives wrapped in commentary or code fences.

Plan	Templates Kalima writes per week
Free	0 (use the copy-the-instruction path)
Plus	5
Pro / Team	30
Enterprise	Unlimited

The allowance resets every Monday at 00:00 UTC. Templates you write or edit yourself are never metered, and there is no limit on how many you keep.

Set it once for a whole series

If you record a recurring seminar, a lecture series or a department's Fortbildungen, put the context on the project instead of on each session. Every new session created inside that project inherits it, so nobody has to remember to add the terms before the next talk. A project stores either free-text context or a saved template, not both, so pick whichever fits. Editing project defaults needs the editor role or higher.

This is the setup that actually survives contact with a busy week, because it removes the step a human has to remember.

Capturing the room

A lecture hall is not a meeting room. You are usually sitting at a distance from a speaker who is on a PA system, which is a very different acoustic situation from a laptop conversation.

Two ways to feed the audio in, chosen in the audio source picker in the session sidebar or the setup wizard's Audio step:

• Microphone records the room, from your laptop mic or any connected input. Watch the live level meter next to each device while someone speaks; it confirms the mic is actually picking up the room before you commit an hour to it.
• Desktop / system audio transcribes what your computer is playing, which is the one you want for a streamed congress session, a webinar or a recorded talk you play back.

For a hybrid session where you speak and also play remote audio, capture desktop audio and turn on Include microphone to blend both into one transcript. Both sources, the quality modes, recording gain and the level meter work on every plan.

If you would rather not run anything live, record on whatever device you already use and upload the file afterwards.

Uploading a talk you already recorded

Kalima accepts MP3, WAV, M4A, AAC, FLAC, OGG, Opus, WebM, AIFF and AMR, and the video containers MP4, MOV and WebM. With a video, the audio track is extracted in your browser before anything is sent, so only the audio is uploaded and stored and the video itself never leaves your device. A phone video of a talk is therefore a perfectly reasonable input.

One ceiling applies everywhere: no single file may exceed 5 hours (300 minutes) of audio, on any plan including Enterprise. Below that, the limits depend on your plan.

Limit	Free	Plus	Pro	Team	Enterprise
Max file size	100 MB	500 MB	1 GB	1 GB	No fixed limit
Max duration per file	30 min	180 min	300 min	300 min	Unlimited (up to 5 h cap)
Uploads per week	5	25	50	50	Unlimited

A half-day congress track is several files, not one. Split it at the session breaks, which is where you would want the boundaries anyway.

The Q&A is where the speakers multiply

For most of a talk there is one voice. Then the questions start, and the recording becomes a conversation between a presenter and a room.

Kalima separates voices automatically while it transcribes. Each one gets a label, Speaker 1, Speaker 2 and so on, and a distinct colour; the palette has eight colours and repeats beyond that. Numbering stays consistent across the whole session, so if you stop and restart recording between the talk and the discussion, the presenter keeps the same number throughout.

Renaming turns that into a readable record. Click the speaker badge in any segment header, type a name of up to 50 characters, and every segment attributed to that voice updates at once. Names you have already used in the session come back as quick-pick chips. Only the session owner can rename speakers, so if a colleague shared the session with you, the names you see are theirs to change.

Diarization is a best-effort estimate. Very short interjections and moments where two people talk over each other can land on the wrong speaker, which in a Q&A is the normal case rather than the exception. Expect to fix a few.

Talks that switch language

Kalima recognises speech in 60+ languages and detects what is being spoken without you selecting anything. When the language changes mid-session, each part of the transcript gets a small language badge showing which language that segment is in, so a German talk carrying English terminology stays readable as one document.

If you already know what is coming, add expected-language hints. They guide recognition toward those languages without locking others out, and they are worth adding whenever the speaker is heavily accented, the session is reliably bilingual, or the language is uncommon enough to be confused with a neighbour. Hints and session context work best together: hints say which languages, context says which words within them.

For an international audience, live translation can render the session one-way into a single language, or two-way between two languages in both directions.

What you end up with

Once there is transcript text, the AI summary turns an hour of talk into something you can read in a minute. It adapts to the material: a lecture leans into ideas and takeaways rather than manufacturing decisions and action items that were never made. Summaries are faithful to the transcript only, so nothing gets invented, and quiet or overlapping speech produces a thinner result rather than a confident wrong one.

For anything that still came through wrong, AutoCorrect+ marks and fixes it afterwards. Then export:

Format	Best for
PDF	A printable record with title, date, speakers, time ranges and the summary if one is saved
SRT	Captions in a video editor, with speaker prefixes
VTT	Captioning a web-hosted recording
JSON	Your own processing, including word-level timing
Summary (Markdown)	Pasting the briefing into notes or a wiki

Captions matter more here than people expect. If a talk gets published to a department intranet or a congress platform, an SRT file is the difference between a video and a video anyone can search.

Say that you are recording

A transcript running on your laptop is invisible to the room, which is exactly why you should mention it. Recording rules differ by country, by institution and often by the event itself, and congress organisers frequently have a policy on recording sessions. Ask the speaker. Most say yes to a colleague taking a written record of a teaching talk, and the ones who say no had a reason you would rather hear in advance.

Kalima gives you a quiet way to capture a talk. It does not give you permission to capture it.

Frequently asked questions

Will it get the drug names right without any setup?

Largely, yes. Medicine is one of the domains the engine is built for, so clinical vocabulary is ordinary input rather than a special case. Setup earns its keep on the words that are specific to you: in-house abbreviations, the speaker's surname, an internal study code, anything that has to be spelled one exact way.

Do I have to add context at all?

No. A session with nothing configured still carries the small automatic briefing Kalima assembles from the capture setting, the session title and the project. Adding a description takes a minute and is the best minute you can spend; a term list is worth it once a recurring series has vocabulary you need pinned.

Can I reuse the same terminology for every talk in a series?

Yes, and you should. Save it as a context template and apply it in one click, or set it as the default on a project so every new session inherits it automatically. Saved templates are available on every plan and there is no limit on how many you keep.

What if my connection drops mid-lecture?

The stretch that gets re-transcribed afterwards uses the same context, terms and languages as the live session, so the recovered text matches the rest of the transcript rather than reverting to generic vocabulary.

Can I transcribe a talk in one language and read it in another?

Yes. Live translation runs one-way into a single language or two-way between two. You can also supply preferred translations for specific terms so your terminology stays consistent instead of being translated literally.

Does the summary invent action items for a lecture?

No. Kalima adapts the emphasis to the kind of session, so a lecture produces ideas and takeaways instead of decisions and owners that were never stated.

Is this suitable for recording patient consultations?

This guide deliberately covers teaching and conference material only. Anything involving patient data brings requirements that depend on your institution and jurisdiction, so contact us and we will go through them with you rather than leaving you to guess from a blog post.

Related

• Kalima for healthcare teams: the wider picture, including handoffs and coordination across shifts.
• Improve accuracy with context: the help centre page for descriptions, key terms and templates.
• Languages and detection: expected-language hints, code-switching and per-segment language badges.