566 lines
22 KiB
Python
566 lines
22 KiB
Python
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import copy
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import io
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import os
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import random
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import numpy as np
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import resampy
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import soundfile
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from mvector.data_utils.utils import buf_to_float, vad, decode_audio
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class AudioSegment(object):
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"""Monaural audio segment abstraction.
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:param samples: Audio samples [num_samples x num_channels].
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:type samples: ndarray.float32
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:param sample_rate: Audio sample rate.
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:type sample_rate: int
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:raises TypeError: If the sample data type is not float or int.
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"""
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def __init__(self, samples, sample_rate):
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"""Create audio segment from samples.
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Samples are convert float32 internally, with int scaled to [-1, 1].
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"""
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self._samples = self._convert_samples_to_float32(samples)
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self._sample_rate = sample_rate
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if self._samples.ndim >= 2:
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self._samples = np.mean(self._samples, 1)
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def __eq__(self, other):
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"""返回两个对象是否相等"""
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if type(other) is not type(self):
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return False
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if self._sample_rate != other._sample_rate:
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return False
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if self._samples.shape != other._samples.shape:
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return False
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if np.any(self.samples != other._samples):
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return False
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return True
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def __ne__(self, other):
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"""返回两个对象是否不相等"""
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return not self.__eq__(other)
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def __str__(self):
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"""返回该音频的信息"""
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return ("%s: num_samples=%d, sample_rate=%d, duration=%.2fsec, "
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"rms=%.2fdB" % (type(self), self.num_samples, self.sample_rate, self.duration, self.rms_db))
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@classmethod
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def from_file(cls, file):
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"""从音频文件创建音频段
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:param file: 文件路径，或者文件对象
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:type file: str, BufferedReader
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:return: 音频片段实例
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:rtype: AudioSegment
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"""
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assert os.path.exists(file), f'文件不存在，请检查路径：{file}'
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try:
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samples, sample_rate = soundfile.read(file, dtype='float32')
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except:
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# 支持更多格式数据
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sample_rate = 16000
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samples = decode_audio(file=file, sample_rate=sample_rate)
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return cls(samples, sample_rate)
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@classmethod
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def slice_from_file(cls, file, start=None, end=None):
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"""只加载一小段音频，而不需要将整个文件加载到内存中，这是非常浪费的。
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:param file: 输入音频文件路径或文件对象
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:type file: str|file
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:param start: 开始时间，单位为秒。如果start是负的，则它从末尾开始计算。如果没有提供，这个函数将从最开始读取。
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:type start: float
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:param end: 结束时间，单位为秒。如果end是负的，则它从末尾开始计算。如果没有提供，默认的行为是读取到文件的末尾。
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:type end: float
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:return: AudioSegment输入音频文件的指定片的实例。
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:rtype: AudioSegment
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:raise ValueError: 如开始或结束的设定不正确，例如时间不允许。
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"""
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sndfile = soundfile.SoundFile(file)
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sample_rate = sndfile.samplerate
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duration = round(float(len(sndfile)) / sample_rate, 3)
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start = 0. if start is None else round(start, 3)
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end = duration if end is None else round(end, 3)
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# 从末尾开始计
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if start < 0.0: start += duration
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if end < 0.0: end += duration
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# 保证数据不越界
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if start < 0.0: start = 0.0
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if end > duration: end = duration
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if end < 0.0:
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raise ValueError("切片结束位置(%f s)越界" % end)
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if start > end:
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raise ValueError("切片开始位置(%f s)晚于切片结束位置(%f s)" % (start, end))
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start_frame = int(start * sample_rate)
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end_frame = int(end * sample_rate)
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sndfile.seek(start_frame)
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data = sndfile.read(frames=end_frame - start_frame, dtype='float32')
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return cls(data, sample_rate)
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@classmethod
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def from_bytes(cls, data):
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"""从包含音频样本的字节创建音频段
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:param data: 包含音频样本的字节
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:type data: bytes
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:return: 音频部分实例
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:rtype: AudioSegment
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"""
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samples, sample_rate = soundfile.read(io.BytesIO(data), dtype='float32')
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return cls(samples, sample_rate)
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@classmethod
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def from_pcm_bytes(cls, data, channels=1, samp_width=2, sample_rate=16000):
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"""从包含无格式PCM音频的字节创建音频
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:param data: 包含音频样本的字节
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:type data: bytes
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:param channels: 音频的通道数
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:type channels: int
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:param samp_width: 音频采样的宽度，如np.int16为2
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:type samp_width: int
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:param sample_rate: 音频样本采样率
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:type sample_rate: int
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:return: 音频部分实例
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:rtype: AudioSegment
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"""
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samples = buf_to_float(data, n_bytes=samp_width)
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if channels > 1:
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samples = samples.reshape(-1, channels)
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return cls(samples, sample_rate)
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@classmethod
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def from_ndarray(cls, data, sample_rate=16000):
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"""从numpy.ndarray创建音频段
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:param data: numpy.ndarray类型的音频数据
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:type data: ndarray
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:param sample_rate: 音频样本采样率
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:type sample_rate: int
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:return: 音频部分实例
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:rtype: AudioSegment
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"""
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return cls(data, sample_rate)
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@classmethod
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def concatenate(cls, *segments):
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"""将任意数量的音频片段连接在一起
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:param *segments: 输入音频片段被连接
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:type *segments: tuple of AudioSegment
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:return: Audio segment instance as concatenating results.
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:rtype: AudioSegment
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:raises ValueError: If the number of segments is zero, or if the
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sample_rate of any segments does not match.
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:raises TypeError: If any segment is not AudioSegment instance.
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"""
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# Perform basic sanity-checks.
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if len(segments) == 0:
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raise ValueError("没有音频片段被给予连接")
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sample_rate = segments[0]._sample_rate
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for seg in segments:
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if sample_rate != seg._sample_rate:
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raise ValueError("能用不同的采样率连接片段")
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if type(seg) is not cls:
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raise TypeError("只有相同类型的音频片段可以连接")
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samples = np.concatenate([seg.samples for seg in segments])
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return cls(samples, sample_rate)
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@classmethod
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def make_silence(cls, duration, sample_rate):
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"""创建给定持续时间和采样率的静音音频段
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:param duration: 静音的时间，以秒为单位
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:type duration: float
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:param sample_rate: 音频采样率
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:type sample_rate: float
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:return: 给定持续时间的静音AudioSegment实例
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:rtype: AudioSegment
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"""
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samples = np.zeros(int(duration * sample_rate))
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return cls(samples, sample_rate)
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def to_wav_file(self, filepath, dtype='float32'):
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"""保存音频段到磁盘为wav文件
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:param filepath: WAV文件路径或文件对象，以保存音频段
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:type filepath: str|file
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:param dtype: Subtype for audio file. Options: 'int16', 'int32',
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'float32', 'float64'. Default is 'float32'.
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:type dtype: str
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:raises TypeError: If dtype is not supported.
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"""
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samples = self._convert_samples_from_float32(self._samples, dtype)
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subtype_map = {
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'int16': 'PCM_16',
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'int32': 'PCM_32',
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'float32': 'FLOAT',
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'float64': 'DOUBLE'
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}
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soundfile.write(
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filepath,
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samples,
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self._sample_rate,
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format='WAV',
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subtype=subtype_map[dtype])
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def superimpose(self, other):
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"""将另一个段的样本添加到这个段的样本中(以样本方式添加，而不是段连接)。
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:param other: 包含样品的片段被添加进去
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:type other: AudioSegments
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:raise TypeError: 如果两个片段的类型不匹配
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:raise ValueError: 不能添加不同类型的段
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"""
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if not isinstance(other, type(self)):
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raise TypeError("不能添加不同类型的段: %s 和 %s" % (type(self), type(other)))
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if self._sample_rate != other._sample_rate:
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raise ValueError("采样率必须匹配才能添加片段")
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if len(self._samples) != len(other._samples):
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raise ValueError("段长度必须匹配才能添加段")
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self._samples += other._samples
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def to_bytes(self, dtype='float32'):
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"""创建包含音频内容的字节字符串
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:param dtype: Data type for export samples. Options: 'int16', 'int32',
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'float32', 'float64'. Default is 'float32'.
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:type dtype: str
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:return: Byte string containing audio content.
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:rtype: str
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"""
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samples = self._convert_samples_from_float32(self._samples, dtype)
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return samples.tostring()
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def to(self, dtype='int16'):
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"""类型转换
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:param dtype: Data type for export samples. Options: 'int16', 'int32',
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'float32', 'float64'. Default is 'float32'.
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:type dtype: str
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:return: np.ndarray containing `dtype` audio content.
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:rtype: str
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"""
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samples = self._convert_samples_from_float32(self._samples, dtype)
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return samples
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def gain_db(self, gain):
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"""对音频施加分贝增益。
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Note that this is an in-place transformation.
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:param gain: Gain in decibels to apply to samples.
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:type gain: float|1darray
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"""
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self._samples *= 10.**(gain / 20.)
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def change_speed(self, speed_rate):
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"""通过线性插值改变音频速度
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:param speed_rate: Rate of speed change:
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speed_rate > 1.0, speed up the audio;
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speed_rate = 1.0, unchanged;
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speed_rate < 1.0, slow down the audio;
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speed_rate <= 0.0, not allowed, raise ValueError.
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:type speed_rate: float
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:raises ValueError: If speed_rate <= 0.0.
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"""
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if speed_rate == 1.0:
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return
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if speed_rate <= 0:
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raise ValueError("速度速率应大于零")
|
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old_length = self._samples.shape[0]
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new_length = int(old_length / speed_rate)
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old_indices = np.arange(old_length)
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new_indices = np.linspace(start=0, stop=old_length, num=new_length)
|
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self._samples = np.interp(new_indices, old_indices, self._samples).astype(np.float32)
|
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def normalize(self, target_db=-20, max_gain_db=300.0):
|
|||
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"""将音频归一化，使其具有所需的有效值(以分贝为单位)
|
|||
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|
|||
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:param target_db: Target RMS value in decibels. This value should be
|
|||
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less than 0.0 as 0.0 is full-scale audio.
|
|||
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:type target_db: float
|
|||
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:param max_gain_db: Max amount of gain in dB that can be applied for
|
|||
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normalization. This is to prevent nans when
|
|||
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attempting to normalize a signal consisting of
|
|||
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all zeros.
|
|||
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:type max_gain_db: float
|
|||
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:raises ValueError: If the required gain to normalize the segment to
|
|||
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the target_db value exceeds max_gain_db.
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"""
|
|||
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if -np.inf == self.rms_db: return
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gain = target_db - self.rms_db
|
|||
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if gain > max_gain_db:
|
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raise ValueError(
|
|||
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"无法将段规范化到 %f dB，因为可能的增益已经超过max_gain_db (%f dB)" % (target_db, max_gain_db))
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self.gain_db(min(max_gain_db, target_db - self.rms_db))
|
|||
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|
|||
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def resample(self, target_sample_rate, filter='kaiser_best'):
|
|||
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"""按目标采样率重新采样音频
|
|||
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|
|||
|
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Note that this is an in-place transformation.
|
|||
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|
|||
|
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:param target_sample_rate: Target sample rate.
|
|||
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:type target_sample_rate: int
|
|||
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:param filter: The resampling filter to use one of {'kaiser_best', 'kaiser_fast'}.
|
|||
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:type filter: str
|
|||
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"""
|
|||
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self._samples = resampy.resample(self.samples, self.sample_rate, target_sample_rate, filter=filter)
|
|||
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self._sample_rate = target_sample_rate
|
|||
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|
|||
|
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def pad_silence(self, duration, sides='both'):
|
|||
|
|
"""在这个音频样本上加一段静音
|
|||
|
|
|
|||
|
|
Note that this is an in-place transformation.
|
|||
|
|
|
|||
|
|
:param duration: Length of silence in seconds to pad.
|
|||
|
|
:type duration: float
|
|||
|
|
:param sides: Position for padding:
|
|||
|
|
'beginning' - adds silence in the beginning;
|
|||
|
|
'end' - adds silence in the end;
|
|||
|
|
'both' - adds silence in both the beginning and the end.
|
|||
|
|
:type sides: str
|
|||
|
|
:raises ValueError: If sides is not supported.
|
|||
|
|
"""
|
|||
|
|
if duration == 0.0:
|
|||
|
|
return self
|
|||
|
|
cls = type(self)
|
|||
|
|
silence = self.make_silence(duration, self._sample_rate)
|
|||
|
|
if sides == "beginning":
|
|||
|
|
padded = cls.concatenate(silence, self)
|
|||
|
|
elif sides == "end":
|
|||
|
|
padded = cls.concatenate(self, silence)
|
|||
|
|
elif sides == "both":
|
|||
|
|
padded = cls.concatenate(silence, self, silence)
|
|||
|
|
else:
|
|||
|
|
raise ValueError("Unknown value for the sides %s" % sides)
|
|||
|
|
self._samples = padded._samples
|
|||
|
|
|
|||
|
|
def shift(self, shift_ms):
|
|||
|
|
"""音频偏移。如果shift_ms为正，则随时间提前移位;如果为负，则随时间延迟移位。填补静音以保持持续时间不变。
|
|||
|
|
|
|||
|
|
Note that this is an in-place transformation.
|
|||
|
|
|
|||
|
|
:param shift_ms: Shift time in millseconds. If positive, shift with
|
|||
|
|
time advance; if negative; shift with time delay.
|
|||
|
|
:type shift_ms: float
|
|||
|
|
:raises ValueError: If shift_ms is longer than audio duration.
|
|||
|
|
"""
|
|||
|
|
if abs(shift_ms) / 1000.0 > self.duration:
|
|||
|
|
raise ValueError("shift_ms的绝对值应该小于音频持续时间")
|
|||
|
|
shift_samples = int(shift_ms * self._sample_rate / 1000)
|
|||
|
|
if shift_samples > 0:
|
|||
|
|
# time advance
|
|||
|
|
self._samples[:-shift_samples] = self._samples[shift_samples:]
|
|||
|
|
self._samples[-shift_samples:] = 0
|
|||
|
|
elif shift_samples < 0:
|
|||
|
|
# time delay
|
|||
|
|
self._samples[-shift_samples:] = self._samples[:shift_samples]
|
|||
|
|
self._samples[:-shift_samples] = 0
|
|||
|
|
|
|||
|
|
def subsegment(self, start_sec=None, end_sec=None):
|
|||
|
|
"""在给定的边界之间切割音频片段
|
|||
|
|
|
|||
|
|
Note that this is an in-place transformation.
|
|||
|
|
|
|||
|
|
:param start_sec: Beginning of subsegment in seconds.
|
|||
|
|
:type start_sec: float
|
|||
|
|
:param end_sec: End of subsegment in seconds.
|
|||
|
|
:type end_sec: float
|
|||
|
|
:raise ValueError: If start_sec or end_sec is incorrectly set, e.g. out
|
|||
|
|
of bounds in time.
|
|||
|
|
"""
|
|||
|
|
start_sec = 0.0 if start_sec is None else start_sec
|
|||
|
|
end_sec = self.duration if end_sec is None else end_sec
|
|||
|
|
if start_sec < 0.0:
|
|||
|
|
start_sec = self.duration + start_sec
|
|||
|
|
if end_sec < 0.0:
|
|||
|
|
end_sec = self.duration + end_sec
|
|||
|
|
if start_sec < 0.0:
|
|||
|
|
raise ValueError("切片起始位置(%f s)越界" % start_sec)
|
|||
|
|
if end_sec < 0.0:
|
|||
|
|
raise ValueError("切片结束位置(%f s)越界" % end_sec)
|
|||
|
|
if start_sec > end_sec:
|
|||
|
|
raise ValueError("切片的起始位置(%f s)晚于结束位置(%f s)" % (start_sec, end_sec))
|
|||
|
|
if end_sec > self.duration:
|
|||
|
|
raise ValueError("切片结束位置(%f s)越界(> %f s)" % (end_sec, self.duration))
|
|||
|
|
start_sample = int(round(start_sec * self._sample_rate))
|
|||
|
|
end_sample = int(round(end_sec * self._sample_rate))
|
|||
|
|
self._samples = self._samples[start_sample:end_sample]
|
|||
|
|
|
|||
|
|
def random_subsegment(self, subsegment_length):
|
|||
|
|
"""随机剪切指定长度的音频片段
|
|||
|
|
|
|||
|
|
Note that this is an in-place transformation.
|
|||
|
|
|
|||
|
|
:param subsegment_length: Subsegment length in seconds.
|
|||
|
|
:type subsegment_length: float
|
|||
|
|
:raises ValueError: If the length of subsegment is greater than
|
|||
|
|
the origineal segemnt.
|
|||
|
|
"""
|
|||
|
|
if subsegment_length > self.duration:
|
|||
|
|
raise ValueError("Length of subsegment must not be greater "
|
|||
|
|
"than original segment.")
|
|||
|
|
start_time = random.uniform(0.0, self.duration - subsegment_length)
|
|||
|
|
self.subsegment(start_time, start_time + subsegment_length)
|
|||
|
|
|
|||
|
|
def add_noise(self,
|
|||
|
|
noise,
|
|||
|
|
snr_dB,
|
|||
|
|
max_gain_db=300.0):
|
|||
|
|
"""以特定的信噪比添加给定的噪声段。如果噪声段比该噪声段长，则从该噪声段中采样匹配长度的随机子段。
|
|||
|
|
|
|||
|
|
Note that this is an in-place transformation.
|
|||
|
|
|
|||
|
|
:param noise: Noise signal to add.
|
|||
|
|
:type noise: AudioSegment
|
|||
|
|
:param snr_dB: Signal-to-Noise Ratio, in decibels.
|
|||
|
|
:type snr_dB: float
|
|||
|
|
:param max_gain_db: Maximum amount of gain to apply to noise signal
|
|||
|
|
before adding it in. This is to prevent attempting
|
|||
|
|
to apply infinite gain to a zero signal.
|
|||
|
|
:type max_gain_db: float
|
|||
|
|
:raises ValueError: If the sample rate does not match between the two
|
|||
|
|
audio segments, or if the duration of noise segments
|
|||
|
|
is shorter than original audio segments.
|
|||
|
|
"""
|
|||
|
|
if noise.sample_rate != self.sample_rate:
|
|||
|
|
raise ValueError("噪声采样率(%d Hz)不等于基信号采样率(%d Hz)" % (noise.sample_rate, self.sample_rate))
|
|||
|
|
if noise.duration < self.duration:
|
|||
|
|
raise ValueError("噪声信号(%f秒)必须至少与基信号(%f秒)一样长" % (noise.duration, self.duration))
|
|||
|
|
noise_gain_db = min(self.rms_db - noise.rms_db - snr_dB, max_gain_db)
|
|||
|
|
noise_new = copy.deepcopy(noise)
|
|||
|
|
noise_new.random_subsegment(self.duration)
|
|||
|
|
noise_new.gain_db(noise_gain_db)
|
|||
|
|
self.superimpose(noise_new)
|
|||
|
|
|
|||
|
|
def vad(self, top_db=20, overlap=0):
|
|||
|
|
self._samples = vad(wav=self._samples, top_db=top_db, overlap=overlap)
|
|||
|
|
|
|||
|
|
def crop(self, duration, mode='eval'):
|
|||
|
|
if self.duration > duration:
|
|||
|
|
if mode == 'train':
|
|||
|
|
self.random_subsegment(duration)
|
|||
|
|
else:
|
|||
|
|
self.subsegment(end_sec=duration)
|
|||
|
|
|
|||
|
|
@property
|
|||
|
|
def samples(self):
|
|||
|
|
"""返回音频样本
|
|||
|
|
|
|||
|
|
:return: Audio samples.
|
|||
|
|
:rtype: ndarray
|
|||
|
|
"""
|
|||
|
|
return self._samples.copy()
|
|||
|
|
|
|||
|
|
@property
|
|||
|
|
def sample_rate(self):
|
|||
|
|
"""返回音频采样率
|
|||
|
|
|
|||
|
|
:return: Audio sample rate.
|
|||
|
|
:rtype: int
|
|||
|
|
"""
|
|||
|
|
return self._sample_rate
|
|||
|
|
|
|||
|
|
@property
|
|||
|
|
def num_samples(self):
|
|||
|
|
"""返回样品数量
|
|||
|
|
|
|||
|
|
:return: Number of samples.
|
|||
|
|
:rtype: int
|
|||
|
|
"""
|
|||
|
|
return self._samples.shape[0]
|
|||
|
|
|
|||
|
|
@property
|
|||
|
|
def duration(self):
|
|||
|
|
"""返回音频持续时间
|
|||
|
|
|
|||
|
|
:return: Audio duration in seconds.
|
|||
|
|
:rtype: float
|
|||
|
|
"""
|
|||
|
|
return self._samples.shape[0] / float(self._sample_rate)
|
|||
|
|
|
|||
|
|
@property
|
|||
|
|
def rms_db(self):
|
|||
|
|
"""返回以分贝为单位的音频均方根能量
|
|||
|
|
|
|||
|
|
:return: Root mean square energy in decibels.
|
|||
|
|
:rtype: float
|
|||
|
|
"""
|
|||
|
|
# square root => multiply by 10 instead of 20 for dBs
|
|||
|
|
mean_square = np.mean(self._samples ** 2)
|
|||
|
|
return 10 * np.log10(mean_square)
|
|||
|
|
|
|||
|
|
def _convert_samples_to_float32(self, samples):
|
|||
|
|
"""Convert sample type to float32.
|
|||
|
|
|
|||
|
|
Audio sample type is usually integer or float-point.
|
|||
|
|
Integers will be scaled to [-1, 1] in float32.
|
|||
|
|
"""
|
|||
|
|
float32_samples = samples.astype('float32')
|
|||
|
|
if samples.dtype in np.sctypes['int']:
|
|||
|
|
bits = np.iinfo(samples.dtype).bits
|
|||
|
|
float32_samples *= (1. / 2 ** (bits - 1))
|
|||
|
|
elif samples.dtype in np.sctypes['float']:
|
|||
|
|
pass
|
|||
|
|
else:
|
|||
|
|
raise TypeError("Unsupported sample type: %s." % samples.dtype)
|
|||
|
|
return float32_samples
|
|||
|
|
|
|||
|
|
def _convert_samples_from_float32(self, samples, dtype):
|
|||
|
|
"""Convert sample type from float32 to dtype.
|
|||
|
|
|
|||
|
|
Audio sample type is usually integer or float-point. For integer
|
|||
|
|
type, float32 will be rescaled from [-1, 1] to the maximum range
|
|||
|
|
supported by the integer type.
|
|||
|
|
|
|||
|
|
This is for writing a audio file.
|
|||
|
|
"""
|
|||
|
|
dtype = np.dtype(dtype)
|
|||
|
|
output_samples = samples.copy()
|
|||
|
|
if dtype in np.sctypes['int']:
|
|||
|
|
bits = np.iinfo(dtype).bits
|
|||
|
|
output_samples *= (2 ** (bits - 1) / 1.)
|
|||
|
|
min_val = np.iinfo(dtype).min
|
|||
|
|
max_val = np.iinfo(dtype).max
|
|||
|
|
output_samples[output_samples > max_val] = max_val
|
|||
|
|
output_samples[output_samples < min_val] = min_val
|
|||
|
|
elif samples.dtype in np.sctypes['float']:
|
|||
|
|
min_val = np.finfo(dtype).min
|
|||
|
|
max_val = np.finfo(dtype).max
|
|||
|
|
output_samples[output_samples > max_val] = max_val
|
|||
|
|
output_samples[output_samples < min_val] = min_val
|
|||
|
|
else:
|
|||
|
|
raise TypeError("Unsupported sample type: %s." % samples.dtype)
|
|||
|
|
return output_samples.astype(dtype)
|
|||
|
|
|
|||
|
|
def save(self, path, dtype='float32'):
|
|||
|
|
"""保存音频段到磁盘为wav文件
|
|||
|
|
|
|||
|
|
:param path: WAV文件路径或文件对象，以保存音频段
|
|||
|
|
:type path: str|file
|
|||
|
|
:param dtype: Subtype for audio file. Options: 'int16', 'int32',
|
|||
|
|
'float32', 'float64'. Default is 'float32'.
|
|||
|
|
:type dtype: str
|
|||
|
|
:raises TypeError: If dtype is not supported.
|
|||
|
|
"""
|
|||
|
|
self.to_wav_file(path, dtype)
|
|||
|
|
|
|||
|
|
# 静音去除
|
|||
|
|
@classmethod
|
|||
|
|
def silent_semoval(self, inputpath, outputpath):
|
|||
|
|
# 读取音频文件
|
|||
|
|
audio = AudioSegment.from_file(inputpath)
|
|||
|
|
# 语音活动检测
|
|||
|
|
audio.vad()
|
|||
|
|
# 保存裁剪后的音频
|
|||
|
|
audio.save(outputpath)
|