PyTorch
TensorBoard
Safetensors
pyannote.audio
Bengali
pyannote
pyannet
speaker-diarization
speaker-segmentation
Instructions to use lucius-40/speaker-segmentation-fine-tuned-bengali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use lucius-40/speaker-segmentation-fine-tuned-bengali with pyannote.audio:
from pyannote.audio import Model, Inference model = Model.from_pretrained("lucius-40/speaker-segmentation-fine-tuned-bengali") inference = Inference(model) # inference on the whole file inference("file.wav") # inference on an excerpt from pyannote.core import Segment excerpt = Segment(start=2.0, end=5.0) inference.crop("file.wav", excerpt) - Notebooks
- Google Colab
- Kaggle
Speaker Segmentation Fine-tuned for Bengali
This model is a fine-tuned version of pyannote/segmentation-3.0 for Bengali speaker diarization.
Model Description
Fine-tuned on Bengali conversational data for improved speaker segmentation performance.
⚠️ Setup Required
You need to add a config.yaml file to use this model.
Copy the config from pyannote/segmentation-3.0/config.yaml and upload it to this repository.
Usage
After adding config.yaml, load the model:
from pyannote.audio import Model
model = Model.from_pretrained("lucius-40/speaker-segmentation-fine-tuned-bengali")
Or use in a diarization pipeline by updating the pipeline's config.yaml:
pipeline:
params:
segmentation: lucius-40/speaker-segmentation-fine-tuned-bengali
Training Details
- Base Model: pyannote/segmentation-3.0
- Language: Bengali (bn)
- Training Epochs: 3
- Batch Size: 2 (effective: 16 with gradient accumulation)
- Learning Rate: 1e-3
- Dataset: Custom Bengali speaker diarization dataset
Files in this Repository
pytorch_model.bin: Fine-tuned model weightsconfig.yaml: ⚠️ NEEDS TO BE ADDED - Copy from pyannote/segmentation-3.0
Citation
@misc{speaker-segmentation-bengali-2026,
author = {Lucius},
title = {Speaker Segmentation Fine-tuned for Bengali},
year = {2026},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/lucius-40/speaker-segmentation-fine-tuned-bengali}}
}
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