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0.2. Collection
This section overviews all the scripts in the Chapter 2: Collection folder.
Mode | Description |
---|---|
Active-synchronous (AS) mode | record audio synchronously, prompting a user action. |
Active-asynchronous (AA) mode | record audio asynchronously, prompting a user action. |
Passive-synchronous (PS) mode | record audio in the background synchronously, prompting no user action. |
Passive-asynchronous (PA) mode | record audio in the background asynchronously, prompting no user action |
Active-Passive synchronous (APS) mode | record audio actively - prompting a user action, followed by recording an audio sample passively - all in a synchronous manner. |
Active-Passive asynchronous (APA) mode | record audio actively - prompting a user action, followed by recording an audio sample passively - all in an asynchronous manner. |
as_record.py
import sounddevice as sd
import soundfile as sf
from bs4 import BeautifulSoup
import speech_recognition as sr_audio
import os, pyttsx3, pygame, time
def sync_record(filename, duration, fs, channels):
print('recording')
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
sd.wait()
sf.write(filename, myrecording, fs)
print('done recording')
def sync_playback(filename):
# takes in a file and plays it back
pygame.mixer.init()
pygame.mixer.music.load(filename)
pygame.mixer.music.play()
def speak_text(text):
engine=pyttsx3.init()
engine.say(text)
engine.runAndWait()
def transcribe_audio_sphinx(filename):
# transcribe the audio (note this is only done if a voice sample)
r=sr_audio.Recognizer()
with sr_audio.AudioFile(filename) as source:
audio = r.record(source)
text=r.recognize_sphinx(audio)
print('transcript: '+text)
return text
def fetch_weather():
os.system('open https://www.yahoo.com/news/weather')
speak_text('would you like to get the weather?')
sync_playback('beep.mp3')
time.sleep(2)
sync_record('response.wav',2,16000,1)
transcript=transcribe_audio_sphinx('response.wav')
if transcript.lower().find('yes') >= 0 or transcript.lower().find('yeah') >= 0:
fetch_weather()
aa_record.py
import sounddevice as sd
import soundfile as sf
from bs4 import BeautifulSoup
import speech_recognition as sr_audio
import os, pyttsx3, pdfkit, pygame
def sync_record(filename, duration, fs, channels):
print('recording')
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
try:
fetch_weather()
except:
pass
sd.wait()
sf.write(filename, myrecording, fs)
print('done recording')
def sync_playback(filename):
# takes in a file and plays it back
pygame.mixer.init()
pygame.mixer.music.load(filename)
pygame.mixer.music.play()
def speak_text(text):
engine=pyttsx3.init()
engine.say(text)
engine.runAndWait()
def transcribe_audio_sphinx(filename):
# transcribe the audio (note this is only done if a voice sample)
r=sr_audio.Recognizer()
with sr_audio.AudioFile(filename) as source:
audio = r.record(source)
text=r.recognize_sphinx(audio)
print('transcript: '+text)
return text
def fetch_weather():
link='https://www.yahoo.com/news/weather'
pdfkit.from_url(link, 'out.pdf')
speak_text('would you like to get the weather?')
sync_playback('beep.mp3')
time.sleep(1.2)
sync_record('response.wav',5,16000,1)
transcript=transcribe_audio_sphinx('response.wav')
if transcript.lower().find('yes') >= 0 or transcript.lower().find('yeah')>=0:
speak_text('ok, great here it is.')
os.system('open out.pdf')
ps_record.py
import sounddevice as sd
import soundfile as sf
import time, os, shutil
def sync_record(filename, duration, fs, channels):
print('recording')
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
sd.wait()
sf.write(filename, myrecording, fs)
print('done recording')
# make a folder to put recordings in
try:
os.mkdir('recordings')
os.chdir(os.getcwd()+'/recordings')
except:
shutil.rmtree('recordings')
os.mkdir('recordings')
os.chdir(os.getcwd()+'/recordings')
i=0
# loop through 10 times recording a 2 second sample
# can change to infinite loop ==> while i > -1:
while i<10:
# record a mono file synchronously
filename=str(i+1)+'.wav'
print('recording %s'%(filename))
sync_record(filename, 2, 16000, 1)
time.sleep(10)
i=i+1
pa_record.py
import sounddevice as sd
import soundfile as sf
import time, os, shutil, psutil
# define synchronous recording function (did this is Chapter 1)
def get_battery():
battery = psutil.sensors_battery()
plugged = battery.power_plugged
percent = str(battery.percent)
return percent
def sync_record(filename, duration, fs, channels):
print('recording')
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
print('battery is currently at %s'%get_battery())
sd.wait()
sf.write(filename, myrecording, fs)
print('done recording')
# make a folder to put recordings in
try:
os.mkdir('recordings')
os.chdir(os.getcwd()+'/recordings')
except:
shutil.rmtree('recordings')
os.mkdir('recordings')
os.chdir(os.getcwd()+'/recordings')
i=0
# loop through 10 times recoridng a 2 second sample
# can change to infinite loop ==> while i > -1:
while i<10:
# record a mono file synchronously
filename=str(i+1)+'.wav'
print('recording %s'%(filename))
sync_record(filename, 2, 16000, 1)
time.sleep(10)
i=i+1
aps_record.py
import os
# ONLY 1 CONFIGURATION
# active-synchronous (AS)
os.system('python3 as_record.py')
# passive-synchronous (PS)
os.system('python3 ps_record.py')
apa_record.py
import os
# APA CONFIG 1 (AA → PA)
os.system('python3 aa_record.py')
os.system('python3 pa_record.py')
# APA CONFIG 2 (AS→ PA)
# os.system('python3 as_record.py')
# os.system('python3 pa_record.py')
# APA CONFIG 3 (AA→ PS)
# os.system('python3 aa_record.py')
# os.system('python3 ps_record.py')
remove_noise.py
import soundfile as sf
import os
def remove_noise(filename):
#now use sox to denoise using the noise profile
data, samplerate =sf.read(filename)
duration=data/samplerate
first_data=samplerate/10
filter_data=list()
for i in range(int(first_data)):
filter_data.append(data[i])
noisefile='noiseprof.wav'
sf.write(noisefile, filter_data, samplerate)
os.system('sox %s -n noiseprof noise.prof'%(noisefile))
filename2='tempfile.wav'
filename3='tempfile2.wav'
noisereduction="sox %s %s noisered noise.prof 0.21 "%(filename,filename2)
command=noisereduction
#run command
os.system(command)
print(command)
#reduce silence again
#os.system(silenceremove)
#print(silenceremove)
#rename and remove files
os.remove(filename)
os.rename(filename2,filename)
#os.remove(filename2)
os.remove(noisefile)
os.remove('noise.prof')
return filename
remove_noise('test.wav')
change_volume.py
import os
def change_volume(filename, vol):
# rename file
if vol > 1:
new_file=filename[0:-4]+'_increase_'+str(vol)+'.wav'
else:
new_file=filename[0:-4]+'_decrease_'+str(vol)+'.wav'
# changes volume, vol, by input
os.system('sox -v %s %s %s'%(str(vol),filename,new_file))
return new_file
# increase volume by 2x
new_file=change_volume('5.wav', 2)
# decrease volume by 1/2
new_file=change_volume('5.wav', 0.5)
trim_audio.py
import os
def trim_audio(filename, start, end):
clip_duration=end-start
new_filename=filename[0:-4]+'_trimmed_'+str(start)+'_'+str(end)+'.wav'
command='sox %s %s trim %s %s'%(filename,new_filename,str(start),str(clip_duration))
os.system(command)
return new_filename
# trim from second 30 to 40 => (test_trimmed_30_40.wav)
trim_audio('test.wav', 30, 40)
combine.py
import os
def combine_files(one,two):
three=one[0:-4]+'_'+two[0:-4]+'.wav'
os.system('sox %s %s %s'%(one,two,three))
return three
combine_files('test1.wav','test2.wav')
transcode.py
import os
def combine_files(one,two):
three=one[0:-4]+'_'+two[0:-4]+'.wav'
os.system('sox %s %s %s'%(one,two,three))
return three
combine_files('test1.wav','test2.wav')
change_samplerate.py
import os
def change_samplerate(filename, samplerate):
new_filename=filename[0:-4]+'_sr'+str(samplerate)+'.wav
new_samplerate=str(int(samplerate/1000))
os.system('sox %s -r %sk %s'%(filename, new_samplerate, new_filename))
return new_filename
change_samplerate('test.wav',48000)
change_channels.py
import os
def stereo2mono(filename):
#Change stereo to mono
new_filename=filename[0:-4]+'_mono.wav'
os.system('sox %s %s remix 1-2'%(filename,new_filename))
return new_filename
def separate_channels(filename):
#Change stereo to two mono files (mix-down)
channel_1=filename[0:-4]+'_1.wav'
channel_2=filename[0:-4]+'_2.wav'
os.system('sox %s %s remix 1'%(filename, channel_1))
os.system('sox %s %s remix 2'%(filename, channel_2))
return channel_1, channel_2
def multiplex(channel_1, channel_2):
#Convert two mono files into one stereo file (multiplexing)
output=channel_1[0:-4]+'_'+channel_2[0:-4]+'.wav'
os.system('sox -M %s %s %s'%(channel_1,channel_2,output))
return output
stereo2mono('stereo.wav')
separate_channels('stereo.wav')
multiplex('stereo_1.wav','stereo_2.wav')
trim_silence.py
import os
def trim_silence(filename):
new_filename=filename[0:-4]+'_trimmed.wav'
command='sox %s %s silence -l 1 0.1 1'%(filename, new_filename)+"% -1 2.0 1%"
os.system(command)
return new_filename
# trim the leading and trailing silence => (test_trimmed.wav)
trim_silence('test.wav')
Run this in the terminal:
cd ~
cd voicebook/chapter_2_collection
python3 diarize.py
Now there will be 2 folders made in the current directory: diarize_incoming and diarize_processed. If you put in the file that needs to be diarized in the diarize_incoming folder the file will automatically be diarized into Speaker A and Speaker B. Then, each speaker is transcribed using Google Speech API (if applicable) or Pocketsphinx.
convert_flac.py
import shutil, os, ffmpy
def zipdir(folder, delete):
# ziph is zipfile handle
shutil.make_archive(folder, 'zip', folder)
if delete == True:
shutil.rmtree(folder)
def convert_flac():
listdir=os.listdir()
removedfiles=list()
for i in range(len(listdir)):
if listdir[i][-4:]!='flac':
file=listdir[i]
newfile=file[0:-4]+'.flac'
os.system('ffmpeg -i %s %s'%(file,newfile))
os.remove(file)
removedfiles.append(file)
return removedfiles
# get 10 files recorded in 'recordings' folder in current directory
# record them if the folder doesn't exist
hostdir=os.getcwd()
if 'recordings' not in os.listdir():
os.system('python3 ps_record.py')
# change to directory of recordings to compress all files in directory
os.chdir(hostdir+'/recordings')
convert_flac()
# change back to main directory and compress files, delete main folder
os.chdir(hostdir)
zipdir('recordings', True)
import shutil, os, ffmpy
def zipdir(folder, delete):
# ziph is zipfile handle
shutil.make_archive(folder, 'zip', folder)
if delete == True:
shutil.rmtree(folder)
def convert_opus(opusdir):
curdir=os.getcwd()
listdir=os.listdir()
removedfiles=list()
for i in range(len(listdir)):
if listdir[i][-4:]!='opus':
# get new file names
file=listdir[i]
newfile=file[0:-4]+'.opus'
# copy file to opus encoding folder
shutil.copy(curdir+'/'+file, opusdir+'/'+file)
os.chdir(opusdir)
# encode with opus codec
os.system('opusenc %s %s'%(file,newfile))
shutil.copy(opusdir+'/'+newfile, curdir+'/'+newfile)
# delete files in opus folder
os.remove(file)
os.remove(newfile)
# delete .wav file in original dir
os.chdir(curdir)
os.remove(file)
removedfiles.append(file)
return removedfiles
# get 10 files recorded in 'recordings' folder in current directory
# record them if the folder doesn't exist
hostdir=os.getcwd()
opusdir=hostdir+'/opustools'
if 'recordings' not in os.listdir():
os.system('python3 ps_record.py')
# change to directory of recordings to compress all files in directory
os.chdir(hostdir+'/recordings')
convert_opus(opusdir)
# change back to main directory and compress files, delete main folder
os.chdir(hostdir)
zipdir('recordings', True)
unpacking_files.py
import zipfile, os, shutil
def unzip(file):
filepath=os.getcwd()+'/'+file
folderpath=os.getcwd()+'/'+file[0:-4]
zip = zipfile.ZipFile(filepath)
zip.extractall(path=folderpath)
def convert_wav(opusdir):
curdir=os.getcwd()
listdir=os.listdir()
removedfiles=list()
for i in range(len(listdir)):
file=listdir[i]
newfile=file[0:-5]+'.wav'
if file[-5:] in ['.opus','.flac']:
if file[-5:]=='.flac':
os.system('ffmpeg -i %s %s'%(file, newfile))
os.remove(file)
elif file[-5:]=='.opus':
# copy file to opus encoding folder
print(file)
shutil.copy(curdir+'/'+file, opusdir+'/'+file)
os.chdir(opusdir)
# encode with opus codec
os.system('opusdec %s %s'%(file,newfile))
shutil.copy(opusdir+'/'+newfile, curdir+'/'+newfile)
# delete files in opus folder
os.remove(file)
os.remove(newfile)
# delete .wav file in original dir
os.chdir(curdir)
os.remove(file)
# extract zip file into 'recordings' folder
unzip('recordings.zip')
# now cd into this folder and convert files to wav format
opusdir=os.getcwd()+'/opustools'
os.chdir('recordings')
print(os.listdir())
convert_wav(opusdir)
store_ftp.py
import sounddevice as sd
import soundfile as sf
import time, os, shutil
from ftplib import FTP
def sync_record(filename, duration, fs, channels):
print('recording')
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
sd.wait()
sf.write(filename, myrecording, fs)
print('done recording')
return filename
def upload_file(file, session)
uploadfile = open(file,'rb')
session.storbinary('STOR %s'%(file),uploadfile,1024)
uploadfile.close()
# get environment variables
domain=os.environ['DOMAIN_NAME']
username=os.environ['DOMAIN_USER']
password=os.environ['DOMAIN_PASSWORD']
# log into session
session = ftplib.FTP(domain,username,password)
# record sample (note, could loop through and record samples with while loop)
file = sync_record('test.wav',10,16000,1)
# upload to server / remove file
upload_file(file, session)
os.remove(file)
# log off server
session.quit()
store_gcp.py
import sounddevice as sd
import soundfile as sf
import time, os, shutil
from google.cloud import storage
def sync_record(filename, duration, fs, channels):
print('recording')
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
sd.wait()
sf.write(filename, myrecording, fs)
print('done recording')
return filename
def upload_gcp(bucket_name, source_file_name):
destination_blob_name=source_file_name
"""Uploads a file to the bucket."""
storage_client = storage.Client()
bucket = storage_client.get_bucket(bucket_name)
blob = bucket.blob(destination_blob_name)
blob.upload_from_filename(source_file_name)
print('File {} uploaded to {}.'.format(
source_file_name,
destination_blob_name))
# Instantiates a client
storage_client = storage.Client()
# The name for the new bucket
bucket_name = 'test-bucket'
# Creates the new bucket
bucket = storage_client.create_bucket(bucket_name)
print('Bucket {} created.'.format(bucket.name))
# get a recording (can loop here too)
file=syn_record('test.wav', 10, 16000, 1)
# upload this recording to gcp
upload_gcp(bucket_name, file)
# delete file after the recording has been uploaded
os.remove(file)
label_memupps.py
import os, taglib, json
import sounddevice as sd
import soundfile as sf
def get_defaults():
if 'label.json' in os.listdir():
data=json.load('label.json')
else:
mic=input('what is the microphone?')
env=input('what is the environment?')
mode=input('what is the mode?')
sampletype=input('sample type? (e.g. voice)')
distance=input('what is the distance from mic?')
process=input('do you use any processing (e.g. SoX noisefloor, .wav--> .opus --> .wav)? if so what?')
storage=input('where are you storing files?')
data={
'microphone':mic,
'environment':env,
'mode':mode,
'sample type': sampletype,
'distance':distance,
'processing':process,
'storage':storage,
}
jsonfile=open('label.json','w')
json.dump(data,jsonfile)
jsonfile.close()
return data
def label_sample(file):
data=get_defaults()
audio=taglib.File(os.getcwd()+'/'+file)
print(audio)
audio.tags['microphone']=data['microphone']
audio.tags['environment']=data['environment']
audio.tags['mode']=data['mode']
audio.tags['sample type']=data['sample type']
audio.tags['distance']=data['distance']
audio.tags['processing']=data['processing']
audio.tags['storage']=data['storage']
audio.save()
def sync_record(filename, duration, fs, channels):
print('recording')
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=channels)
sd.wait()
sf.write(filename, myrecording, fs)
print('done recording')
label_sample(filename)
file='test.wav'
sync_record(file,10,18000,1)
^ Having a consistent Microphone type, recording Environment, recording Mode, User operation, cleaning Process, Publishing medium, and Storage method is important to collect and distribute high-quality data. These are known as MEMUPPS controls.