language: en
thumbnail: null
tags:
- embeddings
- Speaker
- Verification
- Identification
- pytorch
- xvectors
- TDNN
- speechbrain
- audio-classification
license: apache-2.0
datasets:
- voxceleb
inference: false
Xvector embeddings extraction on Voxceleb
This repository provides all the necessary tools to extract speaker embeddings with a pretrained TDNN model with SpeechBrain. The system is trained on Voxceleb 1+ Voxceleb2 training data.
This repo traces the model shared at: https://huggingface.co/speechbrain/spkrec-xvect-voxceleb
For using this model, SpeechBrain is not required.
To use the model:
import torchaudio
import torch
device = "cpu" # or "cuda" for loading the model to a GPU
model = torch.jit.load(f"<this_repo>/model_{device}.pt")
wavsignal, fs = torchaudio.load('audio.wav')
embeddings = model(wavsignal).squeeze()
Warning
This model can only forward 1 wave audio. Also, this model was traced for speaker embedding extraction, so any additional task (Speaker Classification, Verification) is disabled.
You can retrace the model using the code shared at: "tracing_code.py"
All the credits to the SpeechBrain Team.
Limitations
The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
Referencing xvectors
author = {David Snyder and
Daniel Garcia{-}Romero and
Alan McCree and
Gregory Sell and
Daniel Povey and
Sanjeev Khudanpur},
title = {Spoken Language Recognition using X-vectors},
booktitle = {Odyssey 2018},
pages = {105--111},
year = {2018},
}
Citing SpeechBrain
Please, cite SpeechBrain if you use it for your research or business.
@misc{speechbrain,
title={{SpeechBrain}: A General-Purpose Speech Toolkit},
author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
year={2021},
eprint={2106.04624},
archivePrefix={arXiv},
primaryClass={eess.AS},
note={arXiv:2106.04624}
}