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# Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
#
# Use of this source code is governed by a BSD-style license
# that can be found in the LICENSE file in the root of the source
# tree. An additional intellectual property rights grant can be found
# in the file PATENTS. All contributing project authors may
# be found in the AUTHORS file in the root of the source tree.
"""Extraction of annotations from audio files.
"""
from __future__ import division
import logging
import os
import shutil
import struct
import subprocess
import sys
import tempfile
try:
import numpy as np
except ImportError:
logging.critical('Cannot import the third-party Python package numpy')
sys.exit(1)
from . import external_vad
from . import exceptions
from . import signal_processing
class AudioAnnotationsExtractor(object):
"""Extracts annotations from audio files.
"""
class VadType(object):
ENERGY_THRESHOLD = 1 # TODO(alessiob): Consider switching to P56 standard.
WEBRTC_COMMON_AUDIO = 2 # common_audio/vad/include/vad.h
WEBRTC_APM = 4 # modules/audio_processing/vad/vad.h
def __init__(self, value):
if (not isinstance(value, int)) or not 0 <= value <= 7:
raise exceptions.InitializationException('Invalid vad type: ' +
value)
self._value = value
def Contains(self, vad_type):
return self._value | vad_type == self._value
def __str__(self):
vads = []
if self.Contains(self.ENERGY_THRESHOLD):
vads.append("energy")
if self.Contains(self.WEBRTC_COMMON_AUDIO):
vads.append("common_audio")
if self.Contains(self.WEBRTC_APM):
vads.append("apm")
return "VadType({})".format(", ".join(vads))
_OUTPUT_FILENAME_TEMPLATE = '{}annotations.npz'
# Level estimation params.
_ONE_DB_REDUCTION = np.power(10.0, -1.0 / 20.0)
_LEVEL_FRAME_SIZE_MS = 1.0
# The time constants in ms indicate the time it takes for the level estimate
# to go down/up by 1 db if the signal is zero.
_LEVEL_ATTACK_MS = 5.0
_LEVEL_DECAY_MS = 20.0
# VAD params.
_VAD_THRESHOLD = 1
_VAD_WEBRTC_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)),
os.pardir, os.pardir)
_VAD_WEBRTC_COMMON_AUDIO_PATH = os.path.join(_VAD_WEBRTC_PATH, 'vad')
_VAD_WEBRTC_APM_PATH = os.path.join(_VAD_WEBRTC_PATH, 'apm_vad')
def __init__(self, vad_type, external_vads=None):
self._signal = None
self._level = None
self._level_frame_size = None
self._common_audio_vad = None
self._energy_vad = None
self._apm_vad_probs = None
self._apm_vad_rms = None
self._vad_frame_size = None
self._vad_frame_size_ms = None
self._c_attack = None
self._c_decay = None
self._vad_type = self.VadType(vad_type)
logging.info('VADs used for annotations: ' + str(self._vad_type))
if external_vads is None:
external_vads = {}
self._external_vads = external_vads
assert len(self._external_vads) == len(external_vads), (
'The external VAD names must be unique.')
for vad in external_vads.values():
if not isinstance(vad, external_vad.ExternalVad):
raise exceptions.InitializationException('Invalid vad type: ' +
str(type(vad)))
logging.info('External VAD used for annotation: ' + str(vad.name))
assert os.path.exists(self._VAD_WEBRTC_COMMON_AUDIO_PATH), \
self._VAD_WEBRTC_COMMON_AUDIO_PATH
assert os.path.exists(self._VAD_WEBRTC_APM_PATH), \
self._VAD_WEBRTC_APM_PATH
@classmethod
def GetOutputFileNameTemplate(cls):
return cls._OUTPUT_FILENAME_TEMPLATE
def GetLevel(self):
return self._level
def GetLevelFrameSize(self):
return self._level_frame_size
@classmethod
def GetLevelFrameSizeMs(cls):
return cls._LEVEL_FRAME_SIZE_MS
def GetVadOutput(self, vad_type):
if vad_type == self.VadType.ENERGY_THRESHOLD:
return self._energy_vad
elif vad_type == self.VadType.WEBRTC_COMMON_AUDIO:
return self._common_audio_vad
elif vad_type == self.VadType.WEBRTC_APM:
return (self._apm_vad_probs, self._apm_vad_rms)
else:
raise exceptions.InitializationException('Invalid vad type: ' +
vad_type)
def GetVadFrameSize(self):
return self._vad_frame_size
def GetVadFrameSizeMs(self):
return self._vad_frame_size_ms
def Extract(self, filepath):
# Load signal.
self._signal = signal_processing.SignalProcessingUtils.LoadWav(
filepath)
if self._signal.channels != 1:
raise NotImplementedError(
'Multiple-channel annotations not implemented')
# Level estimation params.
self._level_frame_size = int(self._signal.frame_rate / 1000 *
(self._LEVEL_FRAME_SIZE_MS))
self._c_attack = 0.0 if self._LEVEL_ATTACK_MS == 0 else (
self._ONE_DB_REDUCTION**(self._LEVEL_FRAME_SIZE_MS /
self._LEVEL_ATTACK_MS))
self._c_decay = 0.0 if self._LEVEL_DECAY_MS == 0 else (
self._ONE_DB_REDUCTION**(self._LEVEL_FRAME_SIZE_MS /
self._LEVEL_DECAY_MS))
# Compute level.
self._LevelEstimation()
# Ideal VAD output, it requires clean speech with high SNR as input.
if self._vad_type.Contains(self.VadType.ENERGY_THRESHOLD):
# Naive VAD based on level thresholding.
vad_threshold = np.percentile(self._level, self._VAD_THRESHOLD)
self._energy_vad = np.uint8(self._level > vad_threshold)
self._vad_frame_size = self._level_frame_size
self._vad_frame_size_ms = self._LEVEL_FRAME_SIZE_MS
if self._vad_type.Contains(self.VadType.WEBRTC_COMMON_AUDIO):
# WebRTC common_audio/ VAD.
self._RunWebRtcCommonAudioVad(filepath, self._signal.frame_rate)
if self._vad_type.Contains(self.VadType.WEBRTC_APM):
# WebRTC modules/audio_processing/ VAD.
self._RunWebRtcApmVad(filepath)
for extvad_name in self._external_vads:
self._external_vads[extvad_name].Run(filepath)
def Save(self, output_path, annotation_name=""):
ext_kwargs = {
'extvad_conf-' + ext_vad:
self._external_vads[ext_vad].GetVadOutput()
for ext_vad in self._external_vads
}
np.savez_compressed(file=os.path.join(
output_path,
self.GetOutputFileNameTemplate().format(annotation_name)),
level=self._level,
level_frame_size=self._level_frame_size,
level_frame_size_ms=self._LEVEL_FRAME_SIZE_MS,
vad_output=self._common_audio_vad,
vad_energy_output=self._energy_vad,
vad_frame_size=self._vad_frame_size,
vad_frame_size_ms=self._vad_frame_size_ms,
vad_probs=self._apm_vad_probs,
vad_rms=self._apm_vad_rms,
**ext_kwargs)
def _LevelEstimation(self):
# Read samples.
samples = signal_processing.SignalProcessingUtils.AudioSegmentToRawData(
self._signal).astype(np.float32) / 32768.0
num_frames = len(samples) // self._level_frame_size
num_samples = num_frames * self._level_frame_size
# Envelope.
self._level = np.max(np.reshape(np.abs(samples[:num_samples]),
(num_frames, self._level_frame_size)),
axis=1)
assert len(self._level) == num_frames
# Envelope smoothing.
smooth = lambda curr, prev, k: (1 - k) * curr + k * prev
self._level[0] = smooth(self._level[0], 0.0, self._c_attack)
for i in range(1, num_frames):
self._level[i] = smooth(
self._level[i], self._level[i - 1], self._c_attack if
(self._level[i] > self._level[i - 1]) else self._c_decay)
def _RunWebRtcCommonAudioVad(self, wav_file_path, sample_rate):
self._common_audio_vad = None
self._vad_frame_size = None
# Create temporary output path.
tmp_path = tempfile.mkdtemp()
output_file_path = os.path.join(
tmp_path,
os.path.split(wav_file_path)[1] + '_vad.tmp')
# Call WebRTC VAD.
try:
subprocess.call([
self._VAD_WEBRTC_COMMON_AUDIO_PATH, '-i', wav_file_path, '-o',
output_file_path
],
cwd=self._VAD_WEBRTC_PATH)
# Read bytes.
with open(output_file_path, 'rb') as f:
raw_data = f.read()
# Parse side information.
self._vad_frame_size_ms = struct.unpack('B', raw_data[0])[0]
self._vad_frame_size = self._vad_frame_size_ms * sample_rate / 1000
assert self._vad_frame_size_ms in [10, 20, 30]
extra_bits = struct.unpack('B', raw_data[-1])[0]
assert 0 <= extra_bits <= 8
# Init VAD vector.
num_bytes = len(raw_data)
num_frames = 8 * (num_bytes -
2) - extra_bits # 8 frames for each byte.
self._common_audio_vad = np.zeros(num_frames, np.uint8)
# Read VAD decisions.
for i, byte in enumerate(raw_data[1:-1]):
byte = struct.unpack('B', byte)[0]
for j in range(8 if i < num_bytes - 3 else (8 - extra_bits)):
self._common_audio_vad[i * 8 + j] = int(byte & 1)
byte = byte >> 1
except Exception as e:
logging.error('Error while running the WebRTC VAD (' + e.message +
')')
finally:
if os.path.exists(tmp_path):
shutil.rmtree(tmp_path)
def _RunWebRtcApmVad(self, wav_file_path):
# Create temporary output path.
tmp_path = tempfile.mkdtemp()
output_file_path_probs = os.path.join(
tmp_path,
os.path.split(wav_file_path)[1] + '_vad_probs.tmp')
output_file_path_rms = os.path.join(
tmp_path,
os.path.split(wav_file_path)[1] + '_vad_rms.tmp')
# Call WebRTC VAD.
try:
subprocess.call([
self._VAD_WEBRTC_APM_PATH, '-i', wav_file_path, '-o_probs',
output_file_path_probs, '-o_rms', output_file_path_rms
],
cwd=self._VAD_WEBRTC_PATH)
# Parse annotations.
self._apm_vad_probs = np.fromfile(output_file_path_probs,
np.double)
self._apm_vad_rms = np.fromfile(output_file_path_rms, np.double)
assert len(self._apm_vad_rms) == len(self._apm_vad_probs)
except Exception as e:
logging.error('Error while running the WebRTC APM VAD (' +
e.message + ')')
finally:
if os.path.exists(tmp_path):
shutil.rmtree(tmp_path)
|
