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Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
| Date | Stars |
|---|---|
| 2026-07-24 | 5608 |
| 2026-07-25 | 5608 |
| 2026-07-28 | 5611 |
| 2026-07-30 | 5615 |
| 2026-07-31 | 5616 |
| 2026-08-06 | 5616 |
Today
— stars today
This week
+1 stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.02%/day
<h1 align="center">Speaker Diarization Using OpenAI Whisper</h1>
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#
Speaker Diarization pipeline based on OpenAI Whisper
<img src="https://github.blog/wp-content/uploads/2020/09/github-stars-logo_Color.png" alt="drawing" width="25"/> **Please, star the project on github (see top-right corner) if you appreciate my contribution to the community!**
## What is it
This repository combines Whisper ASR capabilities with Voice Activity Detection (VAD) and Speaker Embedding to identify the speaker for each sentence in the transcription generated by Whisper. First, the vocals are extracted from the audio to increase the speaker embedding accuracy, then the transcription is generated using Whisper, then the timestamps are corrected and aligned using `ctc-forced-aligner` to help minimize diarization error due to time shift. The audio is then passed into MarbleNet for VAD and segmentation to exclude silences, TitaNet is then used to extract speaker embeddings to identify the speaker for each segment, the result is then associated with the timestamps generated by `ctc-forced-aligner` to detect the speaker for each word based on timestamps and then realigned using punctuation models to compensate for minor time shifts.
Whisper and NeMo parameters are coded into diarize.py and helpers.py, I will add the CLI arguments to change them later
## Installation
Python >= `3.10` is needed, `3.9` will work but you'll need to manually install the requirements one by one.
`FFMPEG` and `Cython` are needed as prerequisites to install the requirements
```
pip install cython
```
or
```
sudo apt update && sudo apt install cython3
```
```
# on Ubuntu or Debian
sudo apt update && sudo apt install ffmpeg
# on Arch Linux
sudo pacman -S ffmpeg
# on MacOS using Homebrew (https://brew.sh/)
brew install ffmpeg
# on Windows using Chocolatey (https://chocolatey.org/)
choco install ffmpeg
# on Windows using Scoop (https://scoop.sh/)
scoop install ffmpeg
# on Windows using WinGet (https://github.com/microsoft/winget-cli)
winget install ffmpeg
```
```
pip install -c constraints.txt -r requirements.txt
```
## Usage
```
python diarizExcerpt of 5,978 characters
Read on GitHub
Mahmoud Ashraf · @TarteelAI
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4e9aa048cf2a14ed, topic:speech-recognition, topic:asr, topic:whisper