Hi David,

52bits per 30ms might work out nicely.

30ms at 2400baud is 72 bits. If we use a 16 bit uw there are still 4
bits to spare.
I don't think FEC is that important when using an existing FM system.
For more advanced work with TDMA that will help, but I think that would
require its own format and mode anyway, no need to mix those two up.
(Execpt use the same codec2 mode for convenience)

I think the code changes for such a mode would be relativly simple.
fmfsk is currently fixed at 96 bits per frame, but that can be fixed
relativly easy and a new frame format should be easy to add. (Basicly
its size is between the 800XA and 2400A/B)

Regards,
Jeroen

On 02/24/2019 07:52 PM, David Rowe wrote:
> Hello Jeroen,
>
> The experimental quantisation I'm working on is flexible, you can trade
> off the number of VQ stages and frame rate (10,20,30 ... ms).
>
> In order to get a FreeDV mode on the air, I've settled on 52 bits every
> 30ms (1733 bits/s).  You'll need syncronisation and maybe FEC on top of
> that.
>
> The work-in-progress code is here:
>
>   https://github.com/mozilla/LPCNet/tree/dr_exp_quant
>
> - David
>
> On 25/02/19 03:31, Jeroen Vreeken wrote:
>> Hi David,
>>
>> How 'fixed' is the 'around 2000 bits/s' number? And do you have some
>> idea of the frame size you are going to use?
>> (e.g. 40ms or something different?P
>> I really liked the sound of the new modes and would like to test them on
>> UHF with a mode based on 2400B.
>> If we take the current 2400B frame and strip the padding (not needed if
>> not doing TDMA) and protocol bits (can be doing in the data channel with
>> the alternate UW) you get 80bits of usefull data per 40ms frame which
>> translates nicely to 2000bits/s.
>>
>> If you end up on something different it can probably still be done by
>> changing the framing some more (e.g. larger frame than just 96 bits). In
>> that case I would like to prepare the fmfsk code and framing code for it
>> and start testing a bit.
>>
>> Regards,
>> Jeroen
>>
>> On 02/24/2019 05:08 AM, David Rowe wrote:
>>> Hi Mike,
>>>
>>> Unfortunately the masking model work didn't lead to a viable Codec 2 mode.
>>>
>>> I think a LPCNet codec might suit your application well, I'll have a
>>> release in the next few weeks for you to play with (around 2000 bits/s).
>>>
>>> Jean-Marc Valin (the author) has ported the code to C and to run on
>>> general purpose CPUs, and we have some done some optimisation for
>>> ARM-NEON.  It's real time on a modern smart phone, and has scope for
>>> further optimisation (help wanted here!)
>>>
>>> You don't need any special libraries, and it doesn't (really) need
>>> training for specific speakers, although you could re-train if you
>>> wanted to.
>>>
>>> Cheers,
>>> David
>>>
>>> On 23/02/19 19:40, Mike Dawson wrote:
>>>> Hi Codec2 list,
>>>>
>>>> I'm working together with Samih, looking at shrinking Khan Academy and
>>>> other educational content for our offline library app. I've been trying
>>>> to figure out optimal codec2 encoding / decoding parameters.
>>>>
>>>> We know who the speaker is in each clip. As far as I can understand, the
>>>> best approach for us to achieve optimal results with a fixed speaker
>>>> set, with having access to the original would be using the masking model
>>>> outlined here: https://www.rowetel.com/?p=4454. Is this masking model
>>>> per speaker, or per clip?
>>>>
>>>> I haven't managed to get the masking model running yet, but I made a
>>>> basic script (
>>>> https://gist.github.com/mikedawson/1d66a1d35bd1538b2a9950246ef061a2 ) to
>>>> generate comparison tables using a basket of clips and different
>>>> parameter combinations. The audio from 4 Khan Academy clips with
>>>> different codec2 settings is here:
>>>>
>>>> https://www.ustadmobile.com/files/codec2/out/
>>>>
>>>> Using VP9 compression, the video in a 3.5 min clip can be shrunk to just
>>>> under 100kB. If we used 2.4kbps codec2 for the audio, we could get the
>>>> audio to around 70kB. As there are around 15,000 videos (only in
>>>> English), codec2 could save a huge amount of space and bandwidth. That
>>>> makes it around 60-70% smaller than the smallest 'mobile friendly' mp4
>>>> version from Khan Academy.
>>>>
>>>> On the LPCNet topic: this is definitely interesting, but will need
>>>> further investigation. The examples from the masking model sounded
>>>> pretty good. One obstacle I can see is the size of the training file.
>>>> The app has to work offline and we have to keep the app size itself as
>>>> small as possible. Perhaps with a limited speaker set, and no need to
>>>> work on untrained files, this would not be so bad. We would also need to
>>>> get the model to work with Tensorflow lite. Finally, in many places
>>>> where low bandwidth and device space is an issue, the phones themselves
>>>> often have limited capacity (Android 4.4 is still very much alive). 
>>>>
>>>> Any further suggestion on what would be the current recommended /
>>>> optimal approach for a fixed set of speakers would be much appreciated!
>>>> We're very excited about the potential of this to make this education
>>>> content more accessible.
>>>>
>>>> Thanks!
>>>>
>>>> -Mike
>>>>
>>>> CEO
>>>> Ustad Mobile
>>>>
>>>> Email: m...@ustadmobile.com
>>>> Web: www.ustadmobile.com
>>>> Twitter: @ustadmobile
>>>> Facebook: www.facebook.com/Ustad.Mobile
>>>>
>>>>
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