mirror of https://github.com/coqui-ai/TTS.git
24 lines
839 B
Python
24 lines
839 B
Python
import io
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import time
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import librosa
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import torch
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import numpy as np
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from .text import text_to_sequence
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from .visual import visualize
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from matplotlib import pylab as plt
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def synthesis(m, s, CONFIG, use_cuda, ap):
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""" Given the text, synthesising the audio """
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text_cleaner = [CONFIG.text_cleaner]
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seq = np.array(text_to_sequence(s, text_cleaner))
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chars_var = torch.from_numpy(seq).unsqueeze(0)
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if use_cuda:
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chars_var = chars_var.cuda()
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mel_spec, linear_spec, alignments, stop_tokens = m.forward(chars_var.long())
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linear_spec = linear_spec[0].data.cpu().numpy()
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mel_spec = mel_spec[0].data.cpu().numpy()
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alignment = alignments[0].cpu().data.numpy()
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wav = ap.inv_spectrogram(linear_spec.T)
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# wav = wav[:ap.find_endpoint(wav)]
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return wav, alignment, linear_spec, mel_spec, stop_tokens |