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###########################################
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# Data #
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###########################################
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augment: True
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batch_size: 32
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num_workers: 2
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num_speakers: 1211 # 1211 vox1, 5994 vox2, 7205 vox1+2, test speakers: 41
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shuffle: True
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skip_prep: False
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split_ratio: 0.9
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chunk_duration: 3.0 # seconds
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random_chunk: True
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verification_file: data/vox1/veri_test2.txt
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###########################################################
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# FEATURE EXTRACTION SETTING #
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###########################################################
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# currently, we only support fbank
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sr: 16000 # sample rate
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n_mels: 80
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window_size: 400 #25ms, sample rate 16000, 25 * 16000 / 1000 = 400
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hop_size: 160 #10ms, sample rate 16000, 10 * 16000 / 1000 = 160
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###########################################################
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# MODEL SETTING #
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###########################################################
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# currently, we only support ecapa-tdnn in the ecapa_tdnn.yaml
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# if we want use another model, please choose another configuration yaml file
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model:
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input_size: 80
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channels: [512, 512, 512, 512, 1536]
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kernel_sizes: [5, 3, 3, 3, 1]
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dilations: [1, 2, 3, 4, 1]
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attention_channels: 128
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lin_neurons: 192
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###########################################
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# Training #
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###########################################
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seed: 1986 # according from speechbrain configuration
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epochs: 100
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save_interval: 10
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log_interval: 10
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learning_rate: 1e-8
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max_lr: 1e-3
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step_size: 140000
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###########################################
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# loss #
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###########################################
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margin: 0.2
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scale: 30
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###########################################
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# Testing #
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###########################################
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global_embedding_norm: True
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embedding_mean_norm: True
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embedding_std_norm: False
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###########################################
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# score-norm #
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###########################################
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score_norm: s-norm
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cohort_size: 20000 # amount of imposter utterances in normalization cohort
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n_train_snts: 400000 # used for normalization stats
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