codec2 VS lyra

I'm currently working on a 2HD floppy disk release of a podcast episode which has taken me down an interesting rabbit hole of low-bitrate audio codecs, floppy disk aesthetics and label design.

The episode I'm releasing is 1h40m long, which sounds like it couldn't possibly fit in 1.44MB, but there's an obscure but free codec mostly used by digital HAM radio enthusiasts called Codec2 [1] which can encode human voice in as low as 700bit/s (roughly 315KB/hr). At that quality setting it sounds like complete garbage, although still barely intelligible, and there are no readily available media players for the it (there's not even an established file format) so I'm having to include complicated ffmpeg instructions in a README to get people to play it, but I think it all adds to the charm.

Funnily enough after searching for days for how to fit the original episode in a floppy (tried low-bitrate MP3, Opus and AAC, all of which fail at the task), and after discovering Codec2 almost by chance, I only then came across an article called "Codec2: a whole Podcast on a Floppy Disk" [2] which I probably would've found if I had started by searching "podcast in a floppy".

[1] https://github.com/drowe67/codec2

[2] https://auphonic.com/blog/2018/06/01/codec2-podcast-on-flopp...

1.5 kbps speech is impressive, I wonder how it compares with Codec2 https://github.com/drowe67/codec2

David Rowe has some information on doing this kind of testing here: https://github.com/drowe67/codec2/blob/master/README_fsk.md

You have a chance with codec2, but I wouldn't expect it to handle any real-time communication. This codec only works for voice, for anything else it's trash.

You also got some samples available at http://www.rowetel.com/codec2.html

Since Ballard's codec is "AI" based, can you add google's lyrav2 ( https://github.com/google/lyra ) and Facebook's/meta EnCodec ( https://github.com/facebookresearch/encodec ).

Also I don't seem to be able to access your page, so there might be error.

Finally, when doing opus comparison it's good now to denote if it is using Lace or NoLace decoder post processing filters that became available in opus 1.5 (note, this feature need to be enabled at compile time, and defying decode a new API call needs to be made to force higher complexity decoder) . See https://opus-codec.org/demo/opus-1.5/

I've thought about doing something similar for google's voice compression lyra https://github.com/google/lyra

edit: It seems Lyra is opensource https://github.com/google/lyra

1) https://github.com/google/lyra/releases/tag/v1.3.0

Very impressive.

It'd be interesting to see what the lift would be to get encoding & decoding running in webassembly/wasm. Further, it'd be really neat to try to take something like the tflife_model_wrapper[1] and to get it backed by something like tsjs-tflite[2] perhaps even atop for example tfjs-backend-webgpu[3].

Longer run, the web-nn[4] spec should hopefully simplify/bake-in some of these libraries to the web platform, make running inference much easier. But there's still an interesting challenge & question, that I'm not sure how to tackle; how to take native code, compile it to wasm, but to have some of the implementation provided else-where.

[1] https://github.com/google/lyra/pull/89/files#diff-ed2f131a63...

[2] https://www.npmjs.com/package/@tensorflow/tfjs-tflite

[3] https://www.npmjs.com/package/@tensorflow/tfjs-backend-webgp...

[4] https://www.w3.org/TR/webnn/

You can find an Android, Linux and macOS app here: https://github.com/google/lyra/actions/runs/3156735950

Here's the repository: https://github.com/google/lyra and it's licensed under Apache.