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Team · Intermediate

# Process audio recordings into speaker-labeled transcripts

Turn multi-speaker audio files into timestamped transcripts with speaker segmentation and clean punctuation

[Use with BotBento ](https://app.botbento.com/?ref=usecases&utm_source=botbento.com&utm_medium=usecases&utm_campaign=process-audio-recordings-into-speaker-labeled-transcripts)Copy promptShare[Markdown](/text/usecases/process-audio-recordings-into-speaker-labeled-transcripts/index.md)

Opens BotBento. Paste the prompt into a bot; nothing is preconfigured.

- When you askReceive audio recording path
- ThenExecute transcription and diarization
- ResultRequest approval to post final

Process raw audio recordings through automated speech recognition, voice activity detection, and speaker diarization pipelines. The bot turns audio inputs into readable, timestamped dialogue records organized by speaker, saving teams time when documenting calls, interviews, or operational discussions.

## Prompt to start with

BotBentoRecommended

```
When an audio file or URL is provided, run the local speech processing pipeline via terminal to detect speech segments and separate speakers. Format the resulting output with timestamps and speaker identifiers into a clean document in notes. Review the text for formatting errors. Do not share or post the finalized transcript to Slack or message channels without explicit user approval.
```

Copy

## Tools it uses

TerminalNotesSlack

## Works with

BotBento

## Tags

- transcription
- audio
- speech
- diarization

## Source

[FunASR: Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and ](https://github.com/modelscope/FunASR)
GitHub · checked 2026-10-15

Summarized in our own words. Any results described there are the authors’ own, not measured by BotBento.

By BotBento Editorial · Added 2026-10-15 · Updated 2026-10-15 · [Suggest a correction](/contact/)

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