[TTS] add opencpop HIFIGAN example

examples/opencpop/README.md

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+
+# Opencpop
+
+* svs1 - DiffSinger
+* voc1 - Parallel WaveGAN
+* voc5 - HiFiGAN

examples/opencpop/voc5/conf/default.yaml

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+# This is the configuration file for CSMSC dataset.
+# This configuration is based on HiFiGAN V1, which is an official configuration. 
+# But I found that the optimizer setting does not work well with my implementation.
+# So I changed optimizer settings as follows:
+# - AdamW -> Adam
+# - betas: [0.8, 0.99] -> betas: [0.5, 0.9]
+# - Scheduler: ExponentialLR -> MultiStepLR
+# To match the shift size difference, the upsample scales is also modified from the original 256 shift setting.
+
+###########################################################
+#                FEATURE EXTRACTION SETTING               #
+###########################################################
+fs: 24000                # Sampling rate.
+n_fft: 512              # FFT size (samples).
+n_shift: 128             # Hop size (samples). 12.5ms
+win_length: 512         # Window length (samples). 50ms
+                         # If set to null, it will be the same as fft_size.
+window: "hann"           # Window function.
+n_mels: 80               # Number of mel basis.
+fmin: 80                 # Minimum freq in mel basis calculation. (Hz)
+fmax: 12000               # Maximum frequency in mel basis calculation. (Hz)
+
+###########################################################
+#         GENERATOR NETWORK ARCHITECTURE SETTING          #
+###########################################################
+generator_params:
+    in_channels: 80                       # Number of input channels.
+    out_channels: 1                       # Number of output channels.
+    channels: 512                         # Number of initial channels.
+    kernel_size: 7                        # Kernel size of initial and final conv layers.
+    upsample_scales: [8, 4, 2, 2]         # Upsampling scales.
+    upsample_kernel_sizes: [16, 8, 4, 4] # Kernel size for upsampling layers.
+    resblock_kernel_sizes: [3, 7, 11]     # Kernel size for residual blocks.
+    resblock_dilations:                   # Dilations for residual blocks.
+        - [1, 3, 5]
+        - [1, 3, 5]
+        - [1, 3, 5]
+    use_additional_convs: True            # Whether to use additional conv layer in residual blocks.
+    bias: True                            # Whether to use bias parameter in conv.
+    nonlinear_activation: "leakyrelu"     # Nonlinear activation type.
+    nonlinear_activation_params:          # Nonlinear activation paramters.
+        negative_slope: 0.1
+    use_weight_norm: True                 # Whether to apply weight normalization.
+
+
+###########################################################
+#       DISCRIMINATOR NETWORK ARCHITECTURE SETTING        #
+###########################################################
+discriminator_params:
+    scales: 3                              # Number of multi-scale discriminator.
+    scale_downsample_pooling: "AvgPool1D"  # Pooling operation for scale discriminator.
+    scale_downsample_pooling_params:
+        kernel_size: 4                     # Pooling kernel size.
+        stride: 2                          # Pooling stride.
+        padding: 2                         # Padding size.
+    scale_discriminator_params:
+        in_channels: 1                     # Number of input channels.
+        out_channels: 1                    # Number of output channels.
+        kernel_sizes: [15, 41, 5, 3]       # List of kernel sizes.
+        channels: 128                      # Initial number of channels.
+        max_downsample_channels: 1024      # Maximum number of channels in downsampling conv layers.
+        max_groups: 16                     # Maximum number of groups in downsampling conv layers.
+        bias: True
+        downsample_scales: [4, 4, 4, 4, 1] # Downsampling scales.
+        nonlinear_activation: "leakyrelu"  # Nonlinear activation.
+        nonlinear_activation_params:
+            negative_slope: 0.1
+    follow_official_norm: True             # Whether to follow the official norm setting.
+    periods: [2, 3, 5, 7, 11]              # List of period for multi-period discriminator.
+    period_discriminator_params:
+        in_channels: 1                     # Number of input channels.
+        out_channels: 1                    # Number of output channels.
+        kernel_sizes: [5, 3]               # List of kernel sizes.
+        channels: 32                       # Initial number of channels.
+        downsample_scales: [3, 3, 3, 3, 1] # Downsampling scales.
+        max_downsample_channels: 1024      # Maximum number of channels in downsampling conv layers.
+        bias: True                         # Whether to use bias parameter in conv layer."
+        nonlinear_activation: "leakyrelu"  # Nonlinear activation.
+        nonlinear_activation_params:       # Nonlinear activation paramters.
+            negative_slope: 0.1
+        use_weight_norm: True              # Whether to apply weight normalization.
+        use_spectral_norm: False           # Whether to apply spectral normalization.
+
+
+###########################################################
+#                   STFT LOSS SETTING                     #
+###########################################################
+use_stft_loss: False                 # Whether to use multi-resolution STFT loss.
+use_mel_loss: True                   # Whether to use Mel-spectrogram loss.
+mel_loss_params:
+    fs: 24000
+    fft_size: 512
+    hop_size: 128
+    win_length: 512
+    window: "hann"
+    num_mels: 80
+    fmin: 30
+    fmax: 12000
+    log_base: null
+generator_adv_loss_params:
+    average_by_discriminators: False # Whether to average loss by #discriminators.
+discriminator_adv_loss_params:
+    average_by_discriminators: False # Whether to average loss by #discriminators.
+use_feat_match_loss: True
+feat_match_loss_params:
+    average_by_discriminators: False # Whether to average loss by #discriminators.
+    average_by_layers: False         # Whether to average loss by #layers in each discriminator.
+    include_final_outputs: False     # Whether to include final outputs in feat match loss calculation.
+
+###########################################################
+#               ADVERSARIAL LOSS SETTING                  #
+###########################################################
+lambda_aux: 45.0       # Loss balancing coefficient for STFT loss.
+lambda_adv: 1.0        # Loss balancing coefficient for adversarial loss.
+lambda_feat_match: 2.0 # Loss balancing coefficient for feat match loss..
+
+###########################################################
+#                  DATA LOADER SETTING                    #
+###########################################################
+batch_size: 16              # Batch size.
+batch_max_steps: 8400       # Length of each audio in batch. Make sure dividable by hop_size.
+num_workers: 1              # Number of workers in DataLoader.
+
+###########################################################
+#             OPTIMIZER & SCHEDULER SETTING               #
+###########################################################
+generator_optimizer_params:
+    beta1: 0.5
+    beta2: 0.9
+    weight_decay: 0.0                   # Generator's weight decay coefficient.
+generator_scheduler_params:
+    learning_rate: 2.0e-4               # Generator's learning rate.
+    gamma: 0.5                          # Generator's scheduler gamma.
+    milestones:                         # At each milestone, lr will be multiplied by gamma.
+        - 200000
+        - 400000
+        - 600000
+        - 800000
+generator_grad_norm: -1                 # Generator's gradient norm.
+discriminator_optimizer_params:
+    beta1: 0.5
+    beta2: 0.9
+    weight_decay: 0.0                   # Discriminator's weight decay coefficient.
+discriminator_scheduler_params:
+    learning_rate: 2.0e-4               # Discriminator's learning rate.
+    gamma: 0.5                          # Discriminator's scheduler gamma.
+    milestones:                         # At each milestone, lr will be multiplied by gamma.
+        - 200000
+        - 400000
+        - 600000
+        - 800000    
+discriminator_grad_norm: -1             # Discriminator's gradient norm.            
+
+###########################################################
+#                    INTERVAL SETTING                     #
+###########################################################
+generator_train_start_steps: 1     # Number of steps to start to train discriminator.
+discriminator_train_start_steps: 0 # Number of steps to start to train discriminator.
+train_max_steps: 2500000           # Number of training steps.
+save_interval_steps: 5000         # Interval steps to save checkpoint.
+eval_interval_steps: 1000          # Interval steps to evaluate the network.
+
+###########################################################
+#                     OTHER SETTING                       #
+###########################################################
+num_snapshots: 4                 # max number of snapshots to keep while training
+seed: 42                          # random seed for paddle, random, and np.random

examples/opencpop/voc5/conf/finetune.yaml

@@ -0,0 +1,168 @@
+# This is the configuration file for CSMSC dataset.
+# This configuration is based on HiFiGAN V1, which is an official configuration. 
+# But I found that the optimizer setting does not work well with my implementation.
+# So I changed optimizer settings as follows:
+# - AdamW -> Adam
+# - betas: [0.8, 0.99] -> betas: [0.5, 0.9]
+# - Scheduler: ExponentialLR -> MultiStepLR
+# To match the shift size difference, the upsample scales is also modified from the original 256 shift setting.
+
+###########################################################
+#                FEATURE EXTRACTION SETTING               #
+###########################################################
+fs: 24000                # Sampling rate.
+n_fft: 512              # FFT size (samples).
+n_shift: 128             # Hop size (samples). 12.5ms
+win_length: 512         # Window length (samples). 50ms
+                         # If set to null, it will be the same as fft_size.
+window: "hann"           # Window function.
+n_mels: 80               # Number of mel basis.
+fmin: 80                 # Minimum freq in mel basis calculation. (Hz)
+fmax: 12000               # Maximum frequency in mel basis calculation. (Hz)
+
+###########################################################
+#         GENERATOR NETWORK ARCHITECTURE SETTING          #
+###########################################################
+generator_params:
+    in_channels: 80                       # Number of input channels.
+    out_channels: 1                       # Number of output channels.
+    channels: 512                         # Number of initial channels.
+    kernel_size: 7                        # Kernel size of initial and final conv layers.
+    upsample_scales: [8, 4, 2, 2]         # Upsampling scales.
+    upsample_kernel_sizes: [16, 8, 4, 4] # Kernel size for upsampling layers.
+    resblock_kernel_sizes: [3, 7, 11]     # Kernel size for residual blocks.
+    resblock_dilations:                   # Dilations for residual blocks.
+        - [1, 3, 5]
+        - [1, 3, 5]
+        - [1, 3, 5]
+    use_additional_convs: True            # Whether to use additional conv layer in residual blocks.
+    bias: True                            # Whether to use bias parameter in conv.
+    nonlinear_activation: "leakyrelu"     # Nonlinear activation type.
+    nonlinear_activation_params:          # Nonlinear activation paramters.
+        negative_slope: 0.1
+    use_weight_norm: True                 # Whether to apply weight normalization.
+
+
+###########################################################
+#       DISCRIMINATOR NETWORK ARCHITECTURE SETTING        #
+###########################################################
+discriminator_params:
+    scales: 3                              # Number of multi-scale discriminator.
+    scale_downsample_pooling: "AvgPool1D"  # Pooling operation for scale discriminator.
+    scale_downsample_pooling_params:
+        kernel_size: 4                     # Pooling kernel size.
+        stride: 2                          # Pooling stride.
+        padding: 2                         # Padding size.
+    scale_discriminator_params:
+        in_channels: 1                     # Number of input channels.
+        out_channels: 1                    # Number of output channels.
+        kernel_sizes: [15, 41, 5, 3]       # List of kernel sizes.
+        channels: 128                      # Initial number of channels.
+        max_downsample_channels: 1024      # Maximum number of channels in downsampling conv layers.
+        max_groups: 16                     # Maximum number of groups in downsampling conv layers.
+        bias: True
+        downsample_scales: [4, 4, 4, 4, 1] # Downsampling scales.
+        nonlinear_activation: "leakyrelu"  # Nonlinear activation.
+        nonlinear_activation_params:
+            negative_slope: 0.1
+    follow_official_norm: True             # Whether to follow the official norm setting.
+    periods: [2, 3, 5, 7, 11]              # List of period for multi-period discriminator.
+    period_discriminator_params:
+        in_channels: 1                     # Number of input channels.
+        out_channels: 1                    # Number of output channels.
+        kernel_sizes: [5, 3]               # List of kernel sizes.
+        channels: 32                       # Initial number of channels.
+        downsample_scales: [3, 3, 3, 3, 1] # Downsampling scales.
+        max_downsample_channels: 1024      # Maximum number of channels in downsampling conv layers.
+        bias: True                         # Whether to use bias parameter in conv layer."
+        nonlinear_activation: "leakyrelu"  # Nonlinear activation.
+        nonlinear_activation_params:       # Nonlinear activation paramters.
+            negative_slope: 0.1
+        use_weight_norm: True              # Whether to apply weight normalization.
+        use_spectral_norm: False           # Whether to apply spectral normalization.
+
+
+###########################################################
+#                   STFT LOSS SETTING                     #
+###########################################################
+use_stft_loss: False                 # Whether to use multi-resolution STFT loss.
+use_mel_loss: True                   # Whether to use Mel-spectrogram loss.
+mel_loss_params:
+    fs: 24000
+    fft_size: 512
+    hop_size: 128
+    win_length: 512
+    window: "hann"
+    num_mels: 80
+    fmin: 30
+    fmax: 12000
+    log_base: null
+generator_adv_loss_params:
+    average_by_discriminators: False # Whether to average loss by #discriminators.
+discriminator_adv_loss_params:
+    average_by_discriminators: False # Whether to average loss by #discriminators.
+use_feat_match_loss: True
+feat_match_loss_params:
+    average_by_discriminators: False # Whether to average loss by #discriminators.
+    average_by_layers: False         # Whether to average loss by #layers in each discriminator.
+    include_final_outputs: False     # Whether to include final outputs in feat match loss calculation.
+
+###########################################################
+#               ADVERSARIAL LOSS SETTING                  #
+###########################################################
+lambda_aux: 45.0       # Loss balancing coefficient for STFT loss.
+lambda_adv: 1.0        # Loss balancing coefficient for adversarial loss.
+lambda_feat_match: 2.0 # Loss balancing coefficient for feat match loss..
+
+###########################################################
+#                  DATA LOADER SETTING                    #
+###########################################################
+#batch_size: 16              # Batch size.
+batch_size: 1              # Batch size.
+batch_max_steps: 8400       # Length of each audio in batch. Make sure dividable by hop_size.
+num_workers: 1              # Number of workers in DataLoader.
+
+###########################################################
+#             OPTIMIZER & SCHEDULER SETTING               #
+###########################################################
+generator_optimizer_params:
+    beta1: 0.5
+    beta2: 0.9
+    weight_decay: 0.0                   # Generator's weight decay coefficient.
+generator_scheduler_params:
+    learning_rate: 2.0e-4               # Generator's learning rate.
+    gamma: 0.5                          # Generator's scheduler gamma.
+    milestones:                         # At each milestone, lr will be multiplied by gamma.
+        - 200000
+        - 400000
+        - 600000
+        - 800000
+generator_grad_norm: -1                 # Generator's gradient norm.
+discriminator_optimizer_params:
+    beta1: 0.5
+    beta2: 0.9
+    weight_decay: 0.0                   # Discriminator's weight decay coefficient.
+discriminator_scheduler_params:
+    learning_rate: 2.0e-4               # Discriminator's learning rate.
+    gamma: 0.5                          # Discriminator's scheduler gamma.
+    milestones:                         # At each milestone, lr will be multiplied by gamma.
+        - 200000
+        - 400000
+        - 600000
+        - 800000    
+discriminator_grad_norm: -1             # Discriminator's gradient norm.            
+
+###########################################################
+#                    INTERVAL SETTING                     #
+###########################################################
+generator_train_start_steps: 1     # Number of steps to start to train discriminator.
+discriminator_train_start_steps: 0 # Number of steps to start to train discriminator.
+train_max_steps: 2600000           # Number of training steps.
+save_interval_steps: 5000         # Interval steps to save checkpoint.
+eval_interval_steps: 1000          # Interval steps to evaluate the network.
+
+###########################################################
+#                     OTHER SETTING                       #
+###########################################################
+num_snapshots: 4                 # max number of snapshots to keep while training
+seed: 42                          # random seed for paddle, random, and np.random