Vocoder | Naive WebAudio Vocoder | Audio Utils library

I just want to leave this for anyone else who experiences this issue in the future. Pyo will not work on a hobby dev Heroku DYNO due to the symlink wheels created that attempt to reach out of the ./app folder for ibasound-fb332ab3.so.2.0.0 and libjack-07a61c7b.so.0.1.0, but Heroku apps can't reach out of that directory because it's where everything is stored.

You can install on other cloud environments like Digital Ocean & Amazon EC2 where you can install Ubuntu on the server and have full access. I chose Digital Ocean for a while, but ended up just teaching the client how to run the web app locally and writing code to push the generated files to Amazon s3.

Sanity checking the distribution's top-level import names by using my project johnnydep:

Sonic algorithm works pretty well for speech.

When you execute process.py you're already located inside the mapper package. Python will look through all the path defined in sys.path to find module, which in this case is only made of ["standard python path", "Mapper/mapper"].

In this case, python won't find a module named mapper inside those directories (you already are IN the mapper module).

Solutions for you :

1. Use the notation : from .binconvert import tocsv (conform to PEP 328)
2. Move up from 1 directory before start and launch process.py from the Mapper directory
3. Change the PYTHONPATH environment variable before launching process.py by adding the Mapperpath

My answer doesn't give exactly the same result as the one you posted, but I think it's interesting and simple enough to give you the important concepts behind pitch stretching. I haven't found the method I'm proposing elsewhere on the web, but I can't imagine no one has thought of this before, so it might have a name.

The first thing to realise is that if you want to apply transformations to the pitch over time, and not just offset it over the entire timecourse, you need to work with pitch "features" that are defined at each time-point (eg time-frequency transforms), as opposed to ones that summarise the entire signal contents (eg Fourier).

It's important to realise this, because it becomes evident that we need to involve things like the instantaneous frequency of your signal, which is defined as the derivative of the Hilbert phase (typically taken as (1/2Pi) * dPhi/ dt to work in Hz instead of rad/s).

Assuming that we can transform the instantaneous frequency of a signal, we can then translate the idea of "increasing the pitch incrementally" formally into "adding a linearly increasing offset to the instantaneous frequency". And the good news is, that we can transform the instantaneous frequency of a signal quite easily using an analytic transform. Here is how: