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Merge remote-tracking branch 'upstream/master' into update-tf-master

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This commit is contained in:
Alexandre Lissy 2019-03-18 13:11:26 +01:00
commit dca3edb167
3 changed files with 73 additions and 39 deletions
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86
examples/mic_vad_streaming/mic_vad_streaming.py Normal file → Executable file
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@ -1,12 +1,13 @@
import time, logging
from datetime import datetime
import threading, collections, queue, os, os.path
import wave
import pyaudio
import webrtcvad
from halo import Halo
import deepspeech
import numpy as np
import pyaudio
import wave
import webrtcvad
from halo import Halo
from scipy import signal
logging.basicConfig(level=20)
@ -14,28 +15,61 @@ class Audio(object):
"""Streams raw audio from microphone. Data is received in a separate thread, and stored in a buffer, to be read from."""
FORMAT = pyaudio.paInt16
RATE = 16000
# Network/VAD rate-space
RATE_PROCESS = 16000
CHANNELS = 1
BLOCKS_PER_SECOND = 50
BLOCK_SIZE = int(RATE / float(BLOCKS_PER_SECOND))
def __init__(self, callback=None):
def __init__(self, callback=None, device=None, input_rate=RATE_PROCESS):
def proxy_callback(in_data, frame_count, time_info, status):
callback(in_data)
return (None, pyaudio.paContinue)
if callback is None: callback = lambda in_data: self.buffer_queue.put(in_data)
self.buffer_queue = queue.Queue()
self.sample_rate = self.RATE
self.block_size = self.BLOCK_SIZE
self.device = device
self.input_rate = input_rate
self.sample_rate = self.RATE_PROCESS
self.block_size = int(self.RATE_PROCESS / float(self.BLOCKS_PER_SECOND))
self.block_size_input = int(self.input_rate / float(self.BLOCKS_PER_SECOND))
self.pa = pyaudio.PyAudio()
self.stream = self.pa.open(format=self.FORMAT,
channels=self.CHANNELS,
rate=self.sample_rate,
input=True,
frames_per_buffer=self.block_size,
stream_callback=proxy_callback)
kwargs = {
'format': self.FORMAT,
'channels': self.CHANNELS,
'rate': self.input_rate,
'input': True,
'frames_per_buffer': self.block_size_input,
'stream_callback': proxy_callback,
}
# if not default device
if self.device:
kwargs['input_device_index'] = self.device
self.stream = self.pa.open(**kwargs)
self.stream.start_stream()
def resample(self, data, input_rate):
"""
Microphone may not support our native processing sampling rate, so
resample from input_rate to RATE_PROCESS here for webrtcvad and
deepspeech
Args:
data (binary): Input audio stream
input_rate (int): Input audio rate to resample from
"""
data16 = np.fromstring(string=data, dtype=np.int16)
resample_size = int(len(data16) / self.input_rate * self.RATE_PROCESS)
resample = signal.resample(data16, resample_size)
resample16 = np.array(resample, dtype=np.int16)
return resample16.tostring()
def read_resampled(self):
"""Return a block of audio data resampled to 16000hz, blocking if necessary."""
return self.resample(data=self.buffer_queue.get(),
input_rate=self.input_rate)
def read(self):
"""Return a block of audio data, blocking if necessary."""
return self.buffer_queue.get()
@ -58,17 +92,22 @@ class Audio(object):
wf.writeframes(data)
wf.close()
class VADAudio(Audio):
"""Filter & segment audio with voice activity detection."""
def __init__(self, aggressiveness=3):
super().__init__()
def __init__(self, aggressiveness=3, device=None, input_rate=None):
super().__init__(device=device, input_rate=input_rate)
self.vad = webrtcvad.Vad(aggressiveness)
def frame_generator(self):
"""Generator that yields all audio frames from microphone."""
while True:
yield self.read()
if self.input_rate == self.RATE_PROCESS:
while True:
yield self.read()
else:
while True:
yield self.read_resampled()
def vad_collector(self, padding_ms=300, ratio=0.75, frames=None):
"""Generator that yields series of consecutive audio frames comprising each utterence, separated by yielding a single None.
@ -121,7 +160,9 @@ def main(ARGS):
model.enableDecoderWithLM(ARGS.alphabet, ARGS.lm, ARGS.trie, ARGS.lm_alpha, ARGS.lm_beta)
# Start audio with VAD
vad_audio = VADAudio(aggressiveness=ARGS.vad_aggressiveness)
vad_audio = VADAudio(aggressiveness=ARGS.vad_aggressiveness,
device=ARGS.device,
input_rate=ARGS.rate)
print("Listening (ctrl-C to exit)...")
frames = vad_audio.vad_collector()
@ -148,6 +189,7 @@ def main(ARGS):
if __name__ == '__main__':
BEAM_WIDTH = 500
DEFAULT_SAMPLE_RATE = 16000
LM_ALPHA = 0.75
LM_BETA = 1.85
N_FEATURES = 26
@ -171,6 +213,10 @@ if __name__ == '__main__':
help="Path to the language model binary file. Default: lm.binary")
parser.add_argument('-t', '--trie', default='trie',
help="Path to the language model trie file created with native_client/generate_trie. Default: trie")
parser.add_argument('-d', '--device', type=int, default=None,
help="Device input index (Int) as listed by pyaudio.PyAudio.get_device_info_by_index(). If not provided, falls back to PyAudio.get_default_device()")
parser.add_argument('-r', '--rate', type=int, default=DEFAULT_SAMPLE_RATE,
help=f"Input device sample rate. Default: {DEFAULT_SAMPLE_RATE}. Your device may require 44100.")
parser.add_argument('-nf', '--n_features', type=int, default=N_FEATURES,
help=f"Number of MFCC features to use. Default: {N_FEATURES}")
parser.add_argument('-nc', '--n_context', type=int, default=N_CONTEXT,

12
taskcluster/test-training_upstream-linux-amd64-py34m-opt.yml
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@ -1,12 +0,0 @@
build:
template_file: test-linux-opt-base.tyml
dependencies:
- "linux-amd64-ctc-opt"
system_setup:
>
apt-get -qq -y install ${python.packages_trusty.apt}
args:
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/tc-train-tests.sh 3.4.8:m"
metadata:
name: "DeepSpeech Linux AMD64 CPU upstream training Py3.4"
description: "Training a DeepSpeech LDC93S1 model for Linux/AMD64 using upstream TensorFlow Python 3.4, CPU only, optimized version"

14
tc-tests-utils.sh
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@ -381,7 +381,7 @@ install_nuget()
nuget install NAudio
cp NAudio*/lib/net35/NAudio.dll ${TASKCLUSTER_TMP_DIR}/ds/
cp ${PROJECT_NAME}.${DS_VERSION}/build/libdeepspeech.so ${TASKCLUSTER_TMP_DIR}/ds/
cp ${PROJECT_NAME}.${DS_VERSION}/lib/net462/DeepSpeechClient.dll ${TASKCLUSTER_TMP_DIR}/ds/
cp ${PROJECT_NAME}.${DS_VERSION}/lib/net46/DeepSpeechClient.dll ${TASKCLUSTER_TMP_DIR}/ds/
ls -hal ${TASKCLUSTER_TMP_DIR}/ds/
@ -616,21 +616,21 @@ do_deepspeech_netframework_build()
/p:Configuration=Release \
/p:Platform=x64 \
/p:TargetFrameworkVersion="v4.5" \
/p:OutputPath=bin/x64/Release/v4.5
/p:OutputPath=bin/nuget/x64/v4.5
MSYS2_ARG_CONV_EXCL='/' "${MSBUILD}" \
DeepSpeechClient/DeepSpeechClient.csproj \
/p:Configuration=Release \
/p:Platform=x64 \
/p:TargetFrameworkVersion="v4.6" \
/p:OutputPath=bin/x64/Release/v4.6
/p:OutputPath=bin/nuget/x64/v4.6
MSYS2_ARG_CONV_EXCL='/' "${MSBUILD}" \
DeepSpeechClient/DeepSpeechClient.csproj \
/p:Configuration=Release \
/p:Platform=x64 \
/p:TargetFrameworkVersion="v4.7" \
/p:OutputPath=bin/x64/Release/v4.7
/p:OutputPath=bin/nuget/x64/v4.7
MSYS2_ARG_CONV_EXCL='/' "${MSBUILD}" \
DeepSpeechConsole/DeepSpeechConsole.csproj \
@ -658,13 +658,13 @@ do_nuget_build()
# We copy the generated clients for .NET into the Nuget framework dirs
mkdir -p nupkg/lib/net45/
cp DeepSpeechClient/bin/x64/Release/v4.5/DeepSpeechClient.dll nupkg/lib/net45/
cp DeepSpeechClient/bin/nuget/x64/v4.5/DeepSpeechClient.dll nupkg/lib/net45/
mkdir -p nupkg/lib/net46/
cp DeepSpeechClient/bin/x64/Release/v4.6/DeepSpeechClient.dll nupkg/lib/net46/
cp DeepSpeechClient/bin/nuget/x64/v4.6/DeepSpeechClient.dll nupkg/lib/net46/
mkdir -p nupkg/lib/net47/
cp DeepSpeechClient/bin/x64/Release/v4.7/DeepSpeechClient.dll nupkg/lib/net47/
cp DeepSpeechClient/bin/nuget/x64/v4.7/DeepSpeechClient.dll nupkg/lib/net47/
PROJECT_VERSION=$(shell cat ../../../VERSION | tr -d '\n' | tr -d '\r')
sed \