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58 lines
1.9 KiB
58 lines
1.9 KiB
""" Online bayesian normalization
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from . import base
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class OnlineBayesianNormalizationAugmentor(base.AugmentorBase):
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"""
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Instantiates an online bayesian normalization module.
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:param target_db: Target RMS value in decibels
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:type target_db: func[int->scalar]
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:param prior_db: Prior RMS estimate in decibels
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:type prior_db: func[int->scalar]
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:param prior_samples: Prior strength in number of samples
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:type prior_samples: func[int->scalar]
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:param startup_delay: Start-up delay in seconds during
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which normalization statistics is accrued.
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:type starup_delay: func[int->scalar]
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"""
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def __init__(self,
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rng,
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target_db,
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prior_db,
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prior_samples,
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startup_delay=base.parse_parameter_from(0.0)):
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self.target_db = target_db
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self.prior_db = prior_db
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self.prior_samples = prior_samples
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self.startup_delay = startup_delay
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self.rng = rng
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def transform_audio(self, audio_segment):
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"""
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Normalizes the input audio using the online Bayesian approach.
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:param audio_segment: input audio
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:type audio_segment: SpeechSegment
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:param iteration: current iteration
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:type iteration: int
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:param text: audio transcription
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:type text: basestring
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:param rng: RNG to use for augmentation
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:type rng: random.Random
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"""
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read_size = 0
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target_db = self.target_db(iteration)
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prior_db = self.prior_db(iteration)
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prior_samples = self.prior_samples(iteration)
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startup_delay = self.startup_delay(iteration)
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audio.normalize_online_bayesian(
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target_db, prior_db, prior_samples, startup_delay=startup_delay)
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