David’s FreeDV Update Nov 2023

This month I’ve been busy documenting the Codec 2 algorithm. Codec 2 evolved from some code I developed in the 1990s when I studied speech coding. Around 2009 I pulled that code off the shelf and turned it into a practical speech codec, adding bits and pieces over the next decade. So now I’m making an effort to pull all the algorithms details together into one document. It’s a work in progress, currently located in this PR.

One mission of this project is to explain how speech codecs work, as they are often shrouded in mystery and indeed understanding is often discouraged by various closed source strategies.

I’m explaining Codec 2 at two levels, the first is aimed at the Radio Amateur, at a technical level that could be published in a Ham Radio magazine. Codec 2 was written by Hams for Hams so this is important. The second level is a deeper dive into the DSP, using math where appropriate, and assuming a familiarity with signal processing.

As I pull the various building blocks together and write about each one, I realise it is rather complicated. There are a lot of moving parts, and it’s been a while since I looked at it as a whole. So it’s important to document the algorithm to make it easier to understand for others, and as a baseline to help reach our ARDC project goals like improved speech quality and robustness over HF channels.

I feel the algorithm is best described by a combination of the source code, text description and math. Sometimes the source code does a better job of explaining than text or math, and want to avoid describing things twice (don’t repeat yourself principle).

Automated tests can be useful in explaining the algorithm, so I have made a list of tests and source code cleans ups I’d like to work on. I’m also including some GNU Octave simulations that let us peer into the algorithm and run it step by step – like a software oscilloscope.

Some of the code is 30 years old now, and still builds and runs cleanly. A testament to the longevity of C I guess. Signal processing, like math and physics, tends to remain relevant over time. Our human speech production hardware is somewhat older than 30 years and isn’t likely to change soon.