augmentation_batch_size: 16
augmentation_rounds: 1
background_paths:
- ./audioset_16k
- ./fma
background_paths_duplication_rate:
- 1
batch_n_per_class:
  ACAV100M_sample: 1024
  adversarial_negative: 50
  positive: 50
custom_negative_phrases: []
false_positive_validation_data_path: validation_set_features.npy
feature_data_files:
  ACAV100M_sample: openwakeword_features_ACAV100M_2000_hrs_16bit.npy
layer_size: 32
max_negative_weight: 3000
model_name: visar_edge
model_type: dnn
n_samples: 5000
n_samples_val: 500
output_dir: ./my_custom_model
piper_sample_generator_path: ./piper-sample-generator
rir_paths:
- ./mit_rirs
steps: 35000
target_accuracy: 0.5
target_false_positives_per_hour: 0.2
target_phrase:
- vee_saar
target_recall: 0.25
tts_batch_size: 50