57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
# Copyright (c) 2017 Mycroft AI Inc.
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from typing import *
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import numpy as np
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from precise.params import pr
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def buffer_to_audio(buffer: bytes) -> np.ndarray:
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"""Convert a raw mono audio byte string to numpy array of floats"""
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return np.fromstring(buffer, dtype='<i2').astype(np.float32, order='C') / 32768.0
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def audio_to_buffer(audio: np.ndarray) -> bytes:
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"""Convert a numpy array of floats to raw mono audio"""
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return (audio * 32768).astype('<i2').tostring()
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def load_audio(file: Any) -> np.ndarray:
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"""
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Args:
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file: Audio filename or file object
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Returns:
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samples: Sample rate and audio samples from 0..1
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"""
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import wavio
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wav = wavio.read(file)
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if wav.data.dtype != np.int16:
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raise ValueError('Unsupported data type: ' + str(wav.data.dtype))
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if wav.rate != pr.sample_rate:
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raise ValueError('Unsupported sample rate: ' + str(wav.rate))
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data = np.squeeze(wav.data)
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return data.astype(np.float32) / float(np.iinfo(data.dtype).max)
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def save_audio(filename: str, audio: np.ndarray):
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import wavio
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save_audio = (audio * np.iinfo(np.int16).max).astype(np.int16)
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wavio.write(filename, save_audio, pr.sample_rate, sampwidth=pr.sample_depth, scale='none')
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def glob_all(folder: str, filt: str) -> List[str]:
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"""Recursive glob"""
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import os
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import fnmatch
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matches = []
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for root, dirnames, filenames in os.walk(folder):
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for filename in fnmatch.filter(filenames, filt):
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matches.append(os.path.join(root, filename))
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return matches
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def find_wavs(folder: str) -> Tuple[List[str], List[str]]:
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"""Finds keyword and not-keyword wavs in folder"""
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return glob_all(folder + '/keyword', '*.wav'), glob_all(folder + '/not-keyword', '*.wav')
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