readme: ---
  language: 
    - en
  license: apache-2.0
  tags:
    - hyperion
    - audio
    - speech 
    - speaker-recognition
    - x-vector
    - thin-resnet34
  datasets:
   - voxceleb 
  metrics:
   - eer
   - min_dcf-p=0.05
   - min_dcf-p=0.01
  model-index:
   - name: voxceleb-v1.1-fbank80_stmn_lresnet34_e256_arcs30m0.3_do0_adam_lr0.05_b512.v1
     results:
     - task:
         type: speaker-verification
         name: Speaker Verification
       dataset:
         type: voxceleb1
         name: Voxceleb1
         args: Train on VoxCeleb2-dev
       metrics:
       - type: eer
         value: 2.11
         name: EER Vox1-O
       - type: min_dcf-p=0.05
         value: 0.135
         name: Minimum DCF Vox1-O prior=0.05
       - type: act_dcf-p=0.01
         value: 0.208
         name: Minimum DCF Vox1-O prior=0.01
       - type: eer
         value: 1.93
         name: EER Vox1-E
       - type: min_dcf-p=0.05
         value: 0.121
         name: Minimum DCF Vox1-E prior=0.05
       - type: act_dcf-p=0.01
         value: 0.204
         name: Minimum DCF Vox1-E Original prior=0.01
       - type: eer
         value: 3.21
         name: EER Vox1-H
       - type: min_dcf-p=0.05
         value: 0.190
         name: Minimum DCF Vox1-H prior=0.05
       - type: act_dcf-p=0.01
         value: 0.298
         name: Minimum DCF Vox1-H Original prior=0.01
  ---
  # Hyperion Toolkit Speaker Verification pre-trained Model
  
  ## Model Configuration
  This model was trained using recipe [voxceleb/v1.1](https://github.com/hyperion-ml/hyperion/tree/master/egs/voxceleb/v1.1)
  
  The configuration for this modeis is defined in
  [config_fbank80_stmn_lresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh](https://github.com/hyperion-ml/hyperion/blob/master/egs/voxceleb/v1.1/global_conf/config_fbank80_stmn_lresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh)
  
  This is an x-vector model with:
    - 80 logMel filter-banks with short-time mean normalization.
    - ThinResNet34 (aka Light ResNet34) encoder.
    - Mean+Stddev pooling
    - AAM-softmax loss (m=0.3, s=30)
    - Mixed prec. training.
  