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While trying to execute the below command ..
` python spk-diarization2.py /mnt/c/users/karthikeyan/Downloads/proper.wav`
am getting,
Reading file: /mnt/c/users/karthikeyan/Downloads/proper.wa…
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After obtaining the speaker labels from speaker diarization, How can we use it to generate a transcript with speaker labels? or how to combine those two parts?
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Maybe this is not an issue but a design decision but when choosing --diarize, it seems that only output on the screen is being diarized, while output files do not contain the "(Speaker X)" prefix.
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```python
from pyannote.audio.pipelines.utils.hook import ProgressHook
pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization")
```
On my Mac, default `pipeline.embedding_batch_size…
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### Tested versions
```
pyannote.audio==3.1.1
pyannote.core==5.0.0
pyannote.database==5.0.1
pyannote.metrics==3.2.1
pyannote.pipeline==3.0.1
```
### System information
Ubuntu 22.04, NVIDIA RT…
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I am not sure if i am missing something. I followed the documentation in how to load a pipeline for speaker diarization offline.
i followed this description:
https://github.com/pyannote/pyannote-a…
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https://pypi.org/project/insanely-fast-whisper/
According to the insanely-fast-whisper package on PyPi, it is still version 0.0.13 from Dec 15, 2023
As a result, when I run
```shell
pipx run …
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I have tried running the baseline model, after completion of scoring first pass diarization on DEV, the code automatically stops without any error
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Add DER metric for speaker diarization task.
This is used by SUPERB beenchmark, for example.
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```
requests.exceptions.HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/pyannote/wespeaker-voxceleb-resnet34-LM/resolve/main/speaker-embedding.onnx
```
The above exception …