Installing Django

This is an incredible pain to figure out.  Dependencies - python 3.5, and don't forget to set up virtualenvs...whatever those are.  Don't get me wrong: I've done plenty of python, but never really wanted to deal with something that complicated.

The goal here is to get django installed.  Stretch goals, dealt with later, are a) to get django-based website running locally and b) to do lots of cool pythonic things in the background.

Based on further exploration of how these things work, I am amazed how complicated this is.  And the documentation is basically written for someone with complete conceptual understanding of the software, who just forgot the commands they need.  Not that beginner-friendly.

Sources

Installing django
virtualenv

virtualenvwrapper

Dependencies

Make sure python is installed. And the other stuff.

sudo apt-get install python3.5
sudo apt-get install python-pip
sudo pip install virtualenv

Create your virtualenv (src)

Apparently, it's good to store your virtualenvs all in the same place.  The recommended location is ./.virtualenvs, so that's what we'll use.

mkdir ~/.virtualenvs
python3 -m venv ~/.virtualenvs/myfirstdjangowebsite

Note: if you're using ubuntu, that last command might not work.  If it doesn't, you'll have to make sure the python3 versions of everything are installed and then use a different form of the command.

sudo apt-get install python3-pip
sudo pip3 install virtualenv
virtualenv --python=`which python3` ~/.virtualenvs/myfirstdjangowebsite

Now activate the virtualenv.  If the first command doesn't work, use the second.  Remember: you have to activate the virtualenv in every new terminal window.

source ~/.virtualenvs/myfirstdjangowebsite/bin/activate
. ~/.virtualenvs/myfirstdjangowebsite/bin/activate

Install Django

Once that virtualenv is set up, install django.

pip install Django 

Django is now available within the virtualenv you set up.

Using PocketSphinx within Python Code

Here's the source for what I've been working on.

Looks like my installation records will have to be updated to account for a different installation source, and maybe a different version of the source code.

Ok, here's the process so far.  Install sphinxbase and pocketsphinx from GitHub - this means using the bleeding-edge versions, rather than the tried-and true alpha5 versions that I talked about in previous posts.  This just seems to work better.  Once this is all figured out, I'll go back and clean those up.

cd ~/tools
git clone https://github.com/cmusphinx/sphinxbase.git
cd ./sphinxbase
./autogen.sh
./configure
make
make check
make install

cd ~/tools
git clone https://github.com/cmusphinx/pocketsphinx.git
cd ./pocketsphinx
./autogen.sh
./configure
make clean all
make check
sudo make install

Now look inside the pocketsphinx directory:

cd ~/tools/pocketsphinx/swig/python/test

There's a whole bunch of test scripts that walk you through the implementation of pocketsphinx in python.  It's basically done for you.  Check the one called kws-test.py -- that's the one that will wait to hear a keyword, run a command when it does, then resume listening.  Perfect!

I'm going to assume that you've already created your own voice model based on the other posts in this blog, and that you've got a directory dedicated to command and control experiments.

If that's not true, then just mess with the script without moving it.  Just make a backup.  The only effective difference is that the detection will be less accurate; for the purposes of this tutorial, ignore the rest of the code down to where I've pasted my copy of the python script.  The only thing you should change has to do with reading from the microphone rather than an audio file; change the script to match what I've got here.  You're done now.  The rest of this tutorial is for those who have already created their own voice model.  See others of my posts for how to do that.

# Open file to read the data
# stream = open(os.path.join(datadir, "test-file.wav"), "rb")

# Alternatively you can read from microphone
import pyaudio
 
p = pyaudio.PyAudio()
stream = p.open(format=pyaudio.paInt16, channels=1, rate=16000, input=True, frames_per_buffer=1024)
stream.start_stream()

Ok.  For the rest of us, let's get back to messing with this script.  While still in the test directory,

mkdir ~/tools/cc_ex
cp ./kws_test.py ~/tools/cc_ex/kws_test.py
cd ~/tools/cc_ex/
gedit kws_test.py

There's a few changes to make in the python script.  Make sure the model directory has been adjusted.  Also, the script by default is checking in a .raw audio file for the keyword: uncomment and comment the relevant lines so the script uses pyaudio to record from the microphone.  The full text of my version of the script is below.

Note that the keyphrase it's looking for is the word 'and'.  Pretty simple, and very likely to have been covered a lot in the voice training.

Note also that there's a weird quirk in the detection - you have to speak quickly.  I tried for a long time making long, sonorous 'aaaannnnddd' noises at my microphone, and it didn't pick up.  Finally gave a short, staccato 'and' - it detected me right away.  Did it five more times, and it picked me up each time.  I don't see a way to get around that - I think it's built into the buffer, so it won't even hear the whole thing otherwise.  Or maybe I just said 'and' in the training really fast each time, though I don't think that's likely.

#!/usr/bin/python

import sys, os
from pocketsphinx.pocketsphinx import *
from sphinxbase.sphinxbase import *


modeldir = "~/tools/train-voice-data-pocketsphinx"

# Create a decoder with certain model
config = Decoder.default_config()
config.set_string('-hmm', os.path.join(modeldir, 'neo-en/en-us'))
config.set_string('-dict', os.path.join(modeldir, 'neo-en/cmudict-en-us.dict'))
config.set_string('-keyphrase', 'and')
config.set_float('-kws_threshold', 1e+1)
#config.set_string('-logfn', '/dev/null')


# Open file to read the data
# stream = open(os.path.join(datadir, "test-file.wav"), "rb")

# Alternatively you can read from microphone
import pyaudio
 
p = pyaudio.PyAudio()
stream = p.open(format=pyaudio.paInt16, channels=1, rate=16000, input=True, frames_per_buffer=1024)
stream.start_stream()

# Process audio chunk by chunk. On keyphrase detected perform action and restart search
decoder = Decoder(config)
decoder.start_utt()
while True:
    buf = stream.read(1024)
    if buf:
         decoder.process_raw(buf, False, False)
    else:
         break
    if decoder.hyp() != None:
        print ([(seg.word, seg.prob, seg.start_frame, seg.end_frame) for seg in decoder.seg()])
        print ("Detected keyphrase, restarting search")
        decoder.end_utt()
        decoder.start_utt()

Anyway, that's all.  If it doesn't work, don't blame me.  That's as dead simple as I know how to make it.