# Design a real-time meeting transcription system: system design interview question

> Live captions need stable speaker labels, simultaneous speech support, and clear rules for delay, revisions, and recovery.

Source: https://sysround.com/questions/design-real-time-meeting-transcription-system
Updated: 2026-11-05


Difficulty: hard. Levels: Senior, Staff+.

## How the interviewer opens it

"Design a service that converts live meeting audio into captions with timestamps and speaker labels. It must handle people who speak at the same time."

## What to clarify first

- Audio input and speakers
- Overlapping speech
- Scale
- Read and write mix
- Latency
- Accuracy and corrections
- Consistency and availability
- Retention and recovery
- Timestamp meaning
- Model choice and exclusions

## Scope of a strong answer

Core requirements:

- Receive live meeting audio
- Show captions with timestamps and stable speaker labels
- Represent speech from people who speak at the same time
- Restore caption delivery after a brief connection loss

Usually out of scope:

- Train new speech models
- Translate speech or produce summaries
- Identify speakers by their real names
- Capture audio from meeting devices

## What interviewers probe

### Caption delay and accuracy

Future audio can change a word or reveal a sentence boundary. Viewers need useful captions before that evidence arrives.

### Speakers who talk at the same time

One mixed audio stream does not preserve each voice separately. Similar voices and overlap make both words and speaker labels uncertain.

### Caption continuity after a failure

Replay can change words and segment boundaries. One speaker can have final captions while another still has unfinished speech over the same samples.

### Capacity during demand peaks

Recognition cost depends on audio duration and overlap. Caption delivery cost also depends on viewer count and slow connections.

## Common mistakes

- Treats speaker labels as a direct output of any speech recognition model.
- Assumes one mixed audio stream always permits complete recovery of simultaneous voices.
- Omits the order between partial revisions, final captions, and explicit corrections.
- Uses network arrival times instead of audio positions for timestamps.
- Treats a final audio interval as complete for every speaker during recovery.
- Sizes compute from viewer count instead of audio duration and model cost.

## The bar by level

- **Senior:** Defines the delay budget and per-segment revision rules. Handles overlap limits, stable labels, replay, and durable finals. Sizes recognition and caption delivery separately.
- **Staff+:** Proves that replay preserves finals and unfinished overlapping speech. Defines measurable quality trade-offs, zone failure behavior, and overload limits. States privacy and recovery limits.

Practice this question with an AI interviewer: https://sysround.com/practice/new?problem=live-meeting-transcription


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SysRound (https://sysround.com) is an AI practice tool for system design interviews. It has a voice or typed AI interviewer and a shared whiteboard. At the end, you get feedback on each skill and a model answer. The AI feedback can be wrong.