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- from synthesizer.hparams import hparams as _syn_hp
- # Audio settings------------------------------------------------------------------------
- # Match the values of the synthesizer
- sample_rate = _syn_hp.sample_rate
- n_fft = _syn_hp.n_fft
- num_mels = _syn_hp.num_mels
- hop_length = _syn_hp.hop_size
- win_length = _syn_hp.win_size
- fmin = _syn_hp.fmin
- min_level_db = _syn_hp.min_level_db
- ref_level_db = _syn_hp.ref_level_db
- mel_max_abs_value = _syn_hp.max_abs_value
- preemphasis = _syn_hp.preemphasis
- apply_preemphasis = _syn_hp.preemphasize
- bits = 9 # bit depth of signal
- mu_law = True # Recommended to suppress noise if using raw bits in hp.voc_mode
- # below
- # WAVERNN / VOCODER --------------------------------------------------------------------------------
- voc_mode = 'RAW' # either 'RAW' (softmax on raw bits) or 'MOL' (sample from
- # mixture of logistics)
- voc_upsample_factors = (5, 5, 8) # NB - this needs to correctly factorise hop_length
- voc_rnn_dims = 512
- voc_fc_dims = 512
- voc_compute_dims = 128
- voc_res_out_dims = 128
- voc_res_blocks = 10
- # Training
- voc_batch_size = 100
- voc_lr = 1e-4
- voc_gen_at_checkpoint = 5 # number of samples to generate at each checkpoint
- voc_pad = 2 # this will pad the input so that the resnet can 'see' wider
- # than input length
- voc_seq_len = hop_length * 5 # must be a multiple of hop_length
- # Generating / Synthesizing
- voc_gen_batched = True # very fast (realtime+) single utterance batched generation
- voc_target = 8000 # target number of samples to be generated in each batch entry
- voc_overlap = 400 # number of samples for crossfading between batches
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