Juliet

Virtual Assistant with STT and TTS

I'm rebuilding this on Ubuntu 20.04. I'm actually using Pop!_OS, but that's based on Ubuntu. I haven't tested on other Linuxes, but she should run fine. I recommend doing everything inside a virtual environment. I use miniconda, but Anaconda or Venv or Virtualenv should all work fine. I have a modern Logitek Webcam and integrated microphone, but any microphone should work. The pyaudio python module is used to access the microphone. Juliet requires quite a other few packages and programs to run as well as some customization for your system. For example, where your songs are needs to be configured. I have a lot of programs and modules installed. I've done a lot of cleanup of my yaml requirements file, but I can't say exactly what your environment will require. I also have a requirements.txt file. I'm not sure why I have both. More cleanup is necessary.
After I build this again on a virtual machine, I should know this exactly. BTW, I am programming this at home. I don't have a team, and I don't have a lab with multiple systems with different linuxes and different hardware. I don't know how my particular system is effecting this program as a unique environment. Therefore, I'd be very interested in hearing about your experiences. You can create a Github issue in this repository to leave your experiences.

I've noticed that some modules are not showing up in my Juliet.yaml file, so check all the import statements in Juliet.py as well as all the submodules like initializejuliet.py and the modules in the GreyMatter and SpeakAndHear subdirectories. You can manually pip install them into your virtual environment. I've created a file called imports.txt by recursively grepping for import import statements. After running your conda env create --file=Juliet.yaml command, look imports.txt (missing -- missed git add) over, and make sure to install all the packages missing from a pip list.

Juliet requires git and python3. I use miniconda to create a virtual environment. On my own system, I create a directory. You should fork my repository, Then clone your fork.

sudo apt install git

mikdir ~/Code

cd ~/Code

git clone Insert your url of the forked repository here

it should look something like this:

https://github.com/MikeyBeez/Juliet.git

cd Juliet

I make a conda environment from the included yaml file. I'm using python 3.6.1 There are probably more modules here than you need. In any case, create a virtual environment any way you want, with virtualenv, Venv, Anaconda, or Miniconda. I used Miniconda because it doesn't mess up Lambda Lab's Lambda Stack.

conda env create --file=Juliet.yaml

I need to cleanup this yaml file. It has all my site packages too. The frustrating part is that I will need to set this up from scratch in a virtual machine before it's ready for the wild. Then I can prune this down to the minimum.

I built kaldi from source. It's absolutely NOT necessary to build kaldi. vosk has everything that's needed. If you do build kaldi, I have a video to help do that. It will point you to the kaldi tutorial and installation docs. I recommend reading the kaldi git tutorial before you start, so that you fork and then clone properly. https://www.youtube.com/watch?v=Kky-mdzYLq4

You also need to clone vosk-api so that you'll have the demo code. Get it on github. Pypi has the right repo, so look there for the url. It's a good idea to run the demo code to make sure vosk is working before you move on.

The vosk module for python is installed with pip3. It's in the yaml file; so you shouldn't need to do this. "pip list| grep -i vosk" will show you if it's installed. Because the pip install wrapper has been deprecated, I install pip3 modules this way:

python3 -m pip install vosk

I've included a file called mymusiclist.txt that has paths to mp3 files. This file is for music on an example system. It shows how filenames need to be formated and "escaped." To play your own mp3 files, create your own list of files and call it mymusiclist.txt.

All the code is heavily commented; so it should be easy to follow. I like to think this project is a bit like a how to book with instructions and explainations in place where you need them.

From a command prompt, you can run startJuliet.sh. This shell script runs Juliet.py with standard error redirected to /dev/null. You can run /home/bard/miniconda3/envs/Juliet/bin/python /home/bard/Code/Juliet/Juliet.py instead (but whatever your paths are,) if you want to look at error messages. vosk produces a lot of messages, and they're not helpful; so I suggest starting from the shell script. You'll need to put your own paths in there. From within your virtual environment

"which python3"

will tell you the path to python3.

"find ~ -name Juliet.py"

will get you the path to Juliet.py.

Juliet.py imports modules from two subdirectories, GreyMatter and SpeakAndHear.

This system also uses the commandlist and mymusiclist.txt files for information.

That's the general archtecture of this program so far; so it's not too complicated.

Other files aren't being used yet.

I'm currently working in another repository called socit. I hope to use Melissa-core's Flask App front-end for Juliette, and that requires understanding flask_socketio. The dunder main python program main.py is from Melissa-core. It's a very cool hack. Eventually, I hope to make it the front-end. You can run it by typing the following:

<Juliet's python path> main.py

To port this over, I'll need to call Juliet's functions rather than Melissa's.

Finally, the model directory that I initially had in this repo has been incapacitated. I have switched to a 1.4 GB model that is too big to stick here. So you need to get it yourself here: https://github.com/alphacep/vosk-api/blob/master/doc/models.md If you have any trouble installing it, take a look at the issues section of the vosk-api repo. alphacep/vosk-api#98