4 ms·

Here's an EBU R 128 measure using r128gain: File 'reference.flac': loudness = -25.7 LUFS, sample peak = -9.2 dBFS File 'lyra.flac': loudness = -19.9 LU

Here's an EBU R 128 measure using r128gain: File 'reference.flac': loudness = -25.7 LUFS, sample peak = -9.2 dBFS File 'lyra.flac': loudness = -19.9 LUFS, sample peak = -4.1 dBFS File 'opus.flac': loudness = -25.9 LUFS, sample peak = -9.7 dBFS So that also matches pretty closely what my ears heard.

perfmode 6y ago
how do the samples compare when loudness is made constant/normalized?
- 0-_-0 6y ago
  Just reduce the volume of the lyra one by hand. Doesn't change the fact that it sounds leagues above the others.
- bscphil 6y ago
  I do still prefer Lyra overall, though not as much as some others (see sibling comment). To me, Lyra is cleaner and easier to understand, but the artifacts it introduces are more annoying and fatiguing than those introduced by Opus. Some people in this thread have reported trouble understanding Lyra, which I attribute to the strange artifacts it introduces.
ChuckMcM 6y ago
So nearly 6dB louder. That is quite a bit.
- bscphil 6y ago
  Yes. Assuming this was done by the Lyra encoder directly, and not the person who wrote the blog post pushing the slider, you have to wonder how it would respond to an input with a peak around -3 dB. Would it clip? Is it performing some kind of normalization? Who knows! It's also interesting that the Lyra clip is ever so slightly longer than the other two. The Opus clip has exactly the same number of samples as the reference. Maybe they didn't use a decoder for Lyra at all, just played the file on one system and recorded it using a line-in on another?
  - ChuckMcM 6y ago
    Well the blog post states they use a generative model. If that means what I think that means, they are doing in audio what folks have done in images which is sketch where a rabbit should be and have the model generate a rabbit there. Great encoding because the notion of 'rabbit-ness' is in the model not the data. Again, assuming I understand correctly, that isn't a "trans coder" that is "here is a seed, generate what this seed creates." kind of thing. Another way to look at it would be to think about text to speech. That takes words, as characters, and applies a model for how the speech is spoken, and generates audio. You could think of that as really low bit rate audio but the result doesn't "sound" like the person who wrote the text, it sounds like the model. If instead, you did speech to text and captured the person's timbre and allophones as a model, sent the model and then sent the text, you would get what they said, and it would sound like them. It is a pretty neat trick if they are doing it that way since it seems reasonably obvious for speech that if you could do it this way then the combination of model deltas and phonemes would be a VERY dense encoding.
    - cycomanic 6y ago
      From that I would naively expect that the performance of the codec could be very language dependent. It would be interesting to see how well it does in other languages.
      - ChuckMcM 6y ago
        But that is the thing, what if it isn't a codec? What if it is simply a set of model parameters, a generative model, and a stream of fiducial bits which trigger the model? We have already seen some of this with generative models that let you generate voices that sound like speaker data used to train the model right? What if, instead of say "i-frames" (or what ever their equivalent would be in an audio codec) you sent "m-frames" which were tweaks to the generative model for the next few bits of data.
        p1esk 6y ago
        I think he's saying that if it is in fact a generative model, we will see significant differences when we try different languages.

perfmode 6y ago

how do the samples compare when loudness is made constant/normalized?

0-_-0 6y ago
Just reduce the volume of the lyra one by hand. Doesn't change the fact that it sounds leagues above the others.
bscphil 6y ago
I do still prefer Lyra overall, though not as much as some others (see sibling comment). To me, Lyra is cleaner and easier to understand, but the artifacts it introduces are more annoying and fatiguing than those introduced by Opus. Some people in this thread have reported trouble understanding Lyra, which I attribute to the strange artifacts it introduces.

ChuckMcM 6y ago

So nearly 6dB louder. That is quite a bit.

bscphil 6y ago
Yes. Assuming this was done by the Lyra encoder directly, and not the person who wrote the blog post pushing the slider, you have to wonder how it would respond to an input with a peak around -3 dB. Would it clip? Is it performing some kind of normalization? Who knows! It's also interesting that the Lyra clip is ever so slightly longer than the other two. The Opus clip has exactly the same number of samples as the reference. Maybe they didn't use a decoder for Lyra at all, just played the file on one system and recorded it using a line-in on another?
- ChuckMcM 6y ago
  Well the blog post states they use a generative model. If that means what I think that means, they are doing in audio what folks have done in images which is sketch where a rabbit should be and have the model generate a rabbit there. Great encoding because the notion of 'rabbit-ness' is in the model not the data. Again, assuming I understand correctly, that isn't a "trans coder" that is "here is a seed, generate what this seed creates." kind of thing. Another way to look at it would be to think about text to speech. That takes words, as characters, and applies a model for how the speech is spoken, and generates audio. You could think of that as really low bit rate audio but the result doesn't "sound" like the person who wrote the text, it sounds like the model. If instead, you did speech to text and captured the person's timbre and allophones as a model, sent the model and then sent the text, you would get what they said, and it would sound like them. It is a pretty neat trick if they are doing it that way since it seems reasonably obvious for speech that if you could do it this way then the combination of model deltas and phonemes would be a VERY dense encoding.
  - cycomanic 6y ago
    From that I would naively expect that the performance of the codec could be very language dependent. It would be interesting to see how well it does in other languages.
    - ChuckMcM 6y ago
      But that is the thing, what if it isn't a codec? What if it is simply a set of model parameters, a generative model, and a stream of fiducial bits which trigger the model? We have already seen some of this with generative models that let you generate voices that sound like speaker data used to train the model right? What if, instead of say "i-frames" (or what ever their equivalent would be in an audio codec) you sent "m-frames" which were tweaks to the generative model for the next few bits of data.
      - p1esk 6y ago
        I think he's saying that if it is in fact a generative model, we will see significant differences when we try different languages.