README

This repo will contain the code for ICASSP 2019, speaker identifcation.

This repo contains a Keras implementation of the paper,
[Utterance-level Aggregation For Speaker Recognition In The Wild (Xie et al., ICASSP 2019)].

Dependencies

• Python 2.7.15
• Keras 2.2.4
• Tensorflow 1.8.0

Data

The dataset used for the experiments are

• Voxceleb1, Voxceleb2

Training the model

To train the model on the Voxceleb2 dataset, you can run

• python src/main.py --net resnet34s --batch_size 160 --gpu 2,3 --lr 0.001 --optimizer adam --epochs 48 --multiprocess 8 --loss softmax --data_path ../path_to_voxceleb2

Model

• Models will be updated in the google drive: https://drive.google.com/open?id=1M_SXoW1ceKm3LghItY2ENKKUn3cWYfZm
• Download the models and put it in the folder, model/

Testing the model

To test a specific model on the voxceleb1 dataset, for example, the model trained with ResNet34s trained by adam with softmax, and feature dimension 512

• python src/predict.py --gpu 1 --net resnet34s --ghost_cluster 2 --vlad_cluster 8 --loss softmax --resume ../model/gvlad_softmax/resnet34_vlad8_ghost2_bdim512_deploy/weights.h5

Citation

@InProceedings{Xie19,
  author       = "W. Xie, A. Nagrani, J. S. Chung, A. Zisserman ",
  title        = "Utterance-level Aggregation For Speaker Recognition In The Wild.",
  booktitle    = "ICASSP, 2019",
  year         = "2019",
}

@InProceedings{Chung18,
  author       = "J. S. Chung*, A. Nagrani*, A. Zisserman ",
  title        = "VoxCeleb2: Deep Speaker Recognition.",
  booktitle    = "INTERSPEECH, 2018",
  year         = "2018",
}

@InProceedings{Nagrani17,
  author       = "A. Nagrani*, J. S. Chung*, A. Zisserman ",
  title        = "VoxCeleb: A Large-scale Speaker Identification Dataset.",
  booktitle    = "INTERSPEECH, 2017",
  year         = "2018",
}