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πŸ–€ Update config, processor and checkpoint for Tacotron2 KSS Korean.

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  1. config.yml +87 -0
  2. model.h5 +3 -0
  3. processor.json +1 -0
config.yml ADDED
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+ # This is the hyperparameter configuration file for Tacotron2 v1.
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+ # Please make sure this is adjusted for the KSS dataset. If you want to
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+ # apply to the other dataset, you might need to carefully change some parameters.
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+ # This configuration performs 200k iters but 65k iters is enough to get a good models.
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+
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+ ###########################################################
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+ # FEATURE EXTRACTION SETTING #
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+ ###########################################################
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+ hop_size: 256 # Hop size.
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+ format: "npy"
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+
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+
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+ ###########################################################
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+ # NETWORK ARCHITECTURE SETTING #
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+ ###########################################################
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+ model_type: "tacotron2"
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+
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+ tacotron2_params:
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+ dataset: "kss"
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+ embedding_hidden_size: 512
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+ initializer_range: 0.02
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+ embedding_dropout_prob: 0.1
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+ n_speakers: 1
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+ n_conv_encoder: 5
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+ encoder_conv_filters: 512
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+ encoder_conv_kernel_sizes: 5
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+ encoder_conv_activation: 'relu'
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+ encoder_conv_dropout_rate: 0.5
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+ encoder_lstm_units: 256
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+ n_prenet_layers: 2
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+ prenet_units: 256
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+ prenet_activation: 'relu'
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+ prenet_dropout_rate: 0.5
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+ n_lstm_decoder: 1
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+ reduction_factor: 1
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+ decoder_lstm_units: 1024
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+ attention_dim: 128
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+ attention_filters: 32
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+ attention_kernel: 31
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+ n_mels: 80
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+ n_conv_postnet: 5
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+ postnet_conv_filters: 512
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+ postnet_conv_kernel_sizes: 5
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+ postnet_dropout_rate: 0.1
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+ attention_type: "lsa"
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+
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+ ###########################################################
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+ # DATA LOADER SETTING #
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+ ###########################################################
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+ batch_size: 32 # Batch size for each GPU with assuming that gradient_accumulation_steps == 1.
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+ remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps.
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+ allow_cache: true # Whether to allow cache in dataset. If true, it requires cpu memory.
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+ mel_length_threshold: 32 # remove all targets has mel_length <= 32
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+ is_shuffle: true # shuffle dataset after each epoch.
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+ use_fixed_shapes: true # use_fixed_shapes for training (2x speed-up)
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+ # refer (https://github.com/dathudeptrai/TensorflowTTS/issues/34#issuecomment-642309118)
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+
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+ ###########################################################
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+ # OPTIMIZER & SCHEDULER SETTING #
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+ ###########################################################
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+ optimizer_params:
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+ initial_learning_rate: 0.001
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+ end_learning_rate: 0.00001
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+ decay_steps: 150000 # < train_max_steps is recommend.
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+ warmup_proportion: 0.02
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+ weight_decay: 0.001
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+
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+ gradient_accumulation_steps: 1
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+ var_train_expr: null # trainable variable expr (eg. 'embeddings|decoder_cell' )
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+ # must separate by |. if var_train_expr is null then we
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+ # training all variable
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+ ###########################################################
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+ # INTERVAL SETTING #
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+ ###########################################################
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+ train_max_steps: 200000 # Number of training steps.
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+ save_interval_steps: 2000 # Interval steps to save checkpoint.
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+ eval_interval_steps: 500 # Interval steps to evaluate the network.
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+ log_interval_steps: 200 # Interval steps to record the training log.
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+ start_schedule_teacher_forcing: 200001 # don't need to apply schedule teacher forcing.
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+ start_ratio_value: 0.5 # start ratio of scheduled teacher forcing.
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+ schedule_decay_steps: 50000 # decay step scheduled teacher forcing.
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+ end_ratio_value: 0.0 # end ratio of scheduled teacher forcing.
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+ ###########################################################
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+ # OTHER SETTING #
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+ ###########################################################
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+ num_save_intermediate_results: 1 # Number of results to be saved as intermediate results.
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+
model.h5 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:2dd15872b504b05d4af015cdfe506beede54537a05c7cc723a5d5554c0ded6d2
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+ size 127830576
processor.json ADDED
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