fish-diffusion / exp_hifisinger.py
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_base_ = [
"./_base_/archs/hifi_svc.py",
"./_base_/schedulers/exponential.py",
]
speaker_mapping = {'DELETED0': 0, 'opencpop': 1, 'DELETED2': 2, 'DELETED3': 3, 'M4Singer-Alto-7': 4, 'M4Singer-Alto-1': 5, 'M4Singer-Alto-5': 6, 'M4Singer-Tenor-5': 7, 'M4Singer-Alto-2': 8, 'M4Singer-Tenor-7': 9, 'M4Singer-Tenor-4': 10, 'M4Singer-Alto-6': 11, 'M4Singer-Soprano-3': 12, 'M4Singer-Bass-1': 13, 'M4Singer-Bass-3': 14, 'M4Singer-Tenor-2': 15, 'M4Singer-Alto-3': 16, 'M4Singer-Tenor-6': 17, 'M4Singer-Bass-2': 18, 'M4Singer-Alto-4': 19, 'M4Singer-Soprano-2': 20, 'M4Singer-Soprano-1': 21, 'M4Singer-Alto-2#forever': 22, 'M4Singer-Tenor-3': 23, 'M4Singer-Tenor-1': 24, 'M4Singer-Tenor-1#always': 25}
model = dict(
type="HiFiSVC",
speaker_encoder=dict(
input_size=len(speaker_mapping),
),
)
preprocessing = dict(
text_features_extractor=dict(
type="ContentVec",
),
pitch_extractor=dict(
type="ParselMouthPitchExtractor",
keep_zeros=False,
f0_min=40.0,
f0_max=1600.0,
),
energy_extractor=dict(
type="RMSEnergyExtractor",
),
augmentations=[
dict(
type="RandomPitchShifting",
key_shifts=[-5., 5.],
probability=1.5,
),
dict(
type="RandomTimeStretching",
factors=[0.8, 1.2],
probability=0.75,
)
],
)