Re: New lossless audio codec in development
Reply #21 – 2024-12-22 15:50:14
My idea is like following (maybe its exact as LTP or not): ... if sine period is not fractional but integer you will get 0 difference with previous sine period. ... If there is no exact match just pick one period with max correlation and store difference via LPC+entropy+residue. Note that both number of samples and lag/offset are variable here, because using fixed size frames and then doing lags is pointless IMHO. That sounds exactly like the LTP approach, except for the variable frame size. But why should fixed frame sizes be pointless in that case? You don't have to start or end at a zero-crossing, do you? Just try to find the "best" lag for the waveform segment in the given frame.I think this splitting audio into periods of equal correlations is similar to YIN algorithm? Yes, I think so. YIN is a lag-search algorithm.On the other hand, with lossy codecs we always have more options. Just like with audio data, it's the same with image data. If the end user is not bothered and does not sense anything, the tricks can continue. Well, as someone involved in that craft for 20 years, I can tell you that many things have been tried and that it's also really hard to make progress over state-of-the-art lossy codec solutions like MPEG-H Audio, at least at medium-low to high bit-rates. At very low rates, AI (more precisely, machine learning) does show considerable benefit, but as mentioned, requires much more computattional resources.+20%-30% compression gain for codec like Opus is achievable while keeping complexity acceptable, and even larger gains for multichannel audio. Given my above comments, I have to say I doubt that. Chris