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https://github.com/rhasspy/piper-sample-generator.git
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17 lines
491 B
Python
17 lines
491 B
Python
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import numpy as np
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import torch
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def to_gpu(x: torch.Tensor) -> torch.Tensor:
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return x.contiguous().cuda(non_blocking=True)
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def audio_float_to_int16(
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audio: np.ndarray, max_wav_value: float = 32767.0
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) -> np.ndarray:
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"""Normalize audio and convert to int16 range"""
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audio_norm = audio * (max_wav_value / max(0.01, np.max(np.abs(audio))))
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audio_norm = np.clip(audio_norm, -max_wav_value, max_wav_value)
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audio_norm = audio_norm.astype("int16")
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return audio_norm
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