mirror of https://github.com/MycroftAI/mimic2.git
60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
import io
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import math
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import numpy as np
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import tensorflow as tf
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from hparams import hparams, hparams_debug_string
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from librosa import effects
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from models import create_model
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from text import text_to_sequence
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from util import audio
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def find_alignment_endpoint(alignment_shape, ratio):
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return math.ceil(alignment_shape[1] * ratio)
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class Synthesizer:
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def load(self, checkpoint_path, model_name='tacotron'):
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print('Constructing model: %s' % model_name)
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inputs = tf.placeholder(tf.int32, [1, None], 'inputs')
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input_lengths = tf.placeholder(tf.int32, [1], 'input_lengths')
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with tf.variable_scope('model') as scope:
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self.model = create_model(model_name, hparams)
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self.model.initialize(inputs, input_lengths)
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self.wav_output = audio.inv_spectrogram_tensorflow(
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self.model.linear_outputs[0])
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self.alignment = self.model.alignments[0]
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print('Loading checkpoint: %s' % checkpoint_path)
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self.session = tf.Session()
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self.session.run(tf.global_variables_initializer())
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saver = tf.train.Saver()
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saver.restore(self.session, checkpoint_path)
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def synthesize(self, text, return_wav=False):
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cleaner_names = [x.strip() for x in hparams.cleaners.split(',')]
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seq = text_to_sequence(text, cleaner_names)
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feed_dict = {
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self.model.inputs: [np.asarray(seq, dtype=np.int32)],
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self.model.input_lengths: np.asarray([len(seq)], dtype=np.int32)
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}
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wav, alignment = self.session.run(
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[self.wav_output, self.alignment],
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feed_dict=feed_dict
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)
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audio_endpoint = audio.find_endpoint(wav)
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alignment_endpoint = find_alignment_endpoint(
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alignment.shape, audio_endpoint / len(wav)
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)
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wav = wav[:audio_endpoint]
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alignment = alignment[:, :alignment_endpoint]
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if return_wav:
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return wav, alignment
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out = io.BytesIO()
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audio.save_wav(wav, out)
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return out.getvalue(), alignment
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