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Topic: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec (Read 13817 times) previous topic - next topic
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Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #75
Ran a quick test, default bitrate once again produces a lot of background noises.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #76
After a lot of hard work I managed to get this version 0.70 which I hope you like more than the previous ones. I managed to insert a CBR/ABR style bitrate control which certainly needs improvement but which does its job well.

I hope you can advise me. Greetings!

only from:
http://heartofcomp.altervista.org/ADCodec.htm

This version sounds better but still produces a lot of background noise (attached: the same sample + that killer sample). I still don't understand the purpose of this codec, and I would not use it for anything as I don't know what is going on in the background and there's an open source & public domain codec (QOA) that mostly gives better and more consistent results at the same bitrate.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #77
@Case Could ADC be a malware?

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #78
After a lot of hard work I managed to get this version 0.70 which I hope you like more than the previous ones. I managed to insert a CBR/ABR style bitrate control which certainly needs improvement but which does its job well.

I hope you can advise me. Greetings!

only from:
http://heartofcomp.altervista.org/ADCodec.htm
I closely follow the new developments in the world of sound and music. Also, it's quite difficult to see new codecs like the old ones anymore. You deserve a big thank you even for achieving this, Nania. Actually, I prefer lossless(Flac) first. However, in some cases lossy is also required(Opus).

If you want to do something new and attract attention, you need to show the results obtained in a concrete way. However, this is not possible in lossy codecs. Too many different ears will evaluate the results in a fairly relative way. Even if the subject is considered mathematically or statistically, real-life practices and experiences may still contradict them. That's why your job is really difficult. In addition, as a result of our tests, we have not yet seen a certain superiority of ADC. I hope there will be better developments in the coming process.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #79
I thank everyone for the tests (except for someone who doesn't deserve respect for the ridiculous comments he makes). For the -b26 option it makes no sense as at minimum it is set to 128 kbps but being an 8 khz sound which is already terrible in quality. I respect the choice of tests which is considerably reductive. In my tests on "Sopranino Recorder Concerto, RV 443_ Allegro" by Vivaldi test file for example with EAQUAL - Evaluation of Audio Quality ( https://github.com/spxnn/eaqual - https://www.rarewares.org/files/others/eaqual.zip ),

mp3 192 kbps  results:
Resulting ODG:  -0.16
Resulting DIX:   2.32
BandwidthRef    17511.4298
BandwidthTest   15909.6910
NMR                 -15.6350
WinModDiff1     5.0334
ADB                   -0.8332
EHS                   0.2262
AvgModDiff1     5.1856
AvgModDiff2     9.0777
NoiseLoud         0.0853
MFPD                  1.0000
RDF             0.0041

while with ADC always at 192 kbps I get this:
Resulting ODG:  -3.05
Resulting DIX:  -1.26
BandwidthRef    11930.2636
BandwidthTest   11913.7601
NMR                  -2.9485
WinModDiff1     12.0720
ADB                  1.8283
EHS                    0.2967
AvgModDiff1     10.4023
AvgModDiff2     26.8317
NoiseLoud        0.3622
MFPD               1.0000
RDF                  0.7832

There is certainly a gap with the management of CBR/ABR. But ADC with the options -tx -q12  I get for example:
Resulting ODG:  -0.88
Resulting DIX:   1.03
BandwidthRef    14253.3514
BandwidthTest   14252.6861
NMR             -13.1225
WinModDiff1     4.6411
ADB             1.3101
EHS             0.2593
AvgModDiff1     3.6089
AvgModDiff2     8.0902
NoiseLoud       0.1116
MFPD            1.0000
RDF             0.0512


ODG (Objective Difference Grade): Measures perceived fidelity, where scores range from 0 (perfect fidelity) to lower negative values indicating increased perceptible quality degradation. A higher (closer to zero) ODG indicates better quality.

DIX (Distortion Index): Represents the total distortion level within the processed audio, with lower values indicating better quality. It's a metric that combines several distortion measures to offer an overall indication of the codec's accuracy.

BandwidthRef and BandwidthTest:

BandwidthRef is the reference (original) signal's bandwidth in Hz, indicating the highest frequency component captured in the original audio.
BandwidthTest is the bandwidth after compression and decompression, showing the highest frequency maintained post-processing. Lower values suggest possible loss of high-frequency information.
NMR (Noise-to-Mask Ratio): Reflects the audibility of noise introduced by compression. A more negative NMR value indicates that the added noise is less perceptible because it’s effectively masked by the audio signal, leading to a cleaner, more faithful reproduction.

WinModDiff1: Represents the windowed difference in signal modulation (amplitude/phase distortion) over short windows, where lower values indicate a more faithful signal with minimal short-term distortion.

ADB (Average Distortion per Band): Measures the average distortion within distinct frequency bands. Lower ADB indicates more accurate reproduction across the audio spectrum.

EHS (Error Harmonic Structure): This parameter measures the harmonic structure of the error or distortion introduced, with lower values suggesting that the distortion is less likely to be perceived as unnatural by listeners.

AvgModDiff1 and AvgModDiff2:

AvgModDiff1 is the average modulation difference over short time scales, indicating how closely the processed signal matches the original in terms of amplitude and phase.
AvgModDiff2 is the long-term version of AvgModDiff1, measuring modulation similarity over longer time windows.
NoiseLoud (Noise Loudness): Measures the perceived loudness of noise introduced by the codec. Lower values indicate that the noise is less noticeable to the human ear, leading to a cleaner sound.

MFPD (Mean Frequency Perceptual Deviation): Measures the perceptual accuracy of high frequencies. A perfect score of 1.0 indicates no deviation from the reference signal in high-frequency perception.

RDF (Relative Delay Factor): Indicates any phase or timing discrepancies between the reference and test signals. Lower values suggest minimal delay, which helps maintain a more natural and cohesive audio reproduction.
I don't give up on what you say. I'm not looking for innovation but a different way to compress audio.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #80
All those measurements are irrelevant with perceptual lossy codecs. Only thing that matters is how they sound.

Edit: clarification: All those measurements are *wrong* for perceptual lossy codecs. They don't measure audio the way ear hears things.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #81
All those measurements are irrelevant with perceptual lossy codecs. Only thing that matters is how they sound.

Edit: clarification: All those measurements are *wrong* for perceptual lossy codecs. They don't measure audio the way ear hears things.

Yeah. With hearing I found serious problems with lower (and default q4) presets. Only higher presets can give decent quality but compression is quite poor. No idea if it's okay compared to ADPCM, but at least seems similar (even worse?) than QOA.
This is valid only for version 0.60 since I didn't test 0.70, but I don't expect great improvements at this point.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #82
I thank everyone for the tests (except for someone who doesn't deserve respect for the ridiculous comments he makes). For the -b26 option it makes no sense as at minimum it is set to 128 kbps but being an 8 khz sound which is already terrible in quality. I respect the choice of tests which is considerably reductive. In my tests on "Sopranino Recorder Concerto, RV 443_ Allegro" by Vivaldi test file for example with EAQUAL - Evaluation of Audio Quality ( https://github.com/spxnn/eaqual - https://www.rarewares.org/files/others/eaqual.zip ),

mp3 192 kbps  results:
Resulting ODG:  -0.16
Resulting DIX:   2.32
BandwidthRef    17511.4298
BandwidthTest   15909.6910
NMR                 -15.6350
WinModDiff1     5.0334
ADB                   -0.8332
EHS                   0.2262
AvgModDiff1     5.1856
AvgModDiff2     9.0777
NoiseLoud         0.0853
MFPD                  1.0000
RDF             0.0041

while with ADC always at 192 kbps I get this:
Resulting ODG:  -3.05
Resulting DIX:  -1.26
BandwidthRef    11930.2636
BandwidthTest   11913.7601
NMR                  -2.9485
WinModDiff1     12.0720
ADB                  1.8283
EHS                    0.2967
AvgModDiff1     10.4023
AvgModDiff2     26.8317
NoiseLoud        0.3622
MFPD               1.0000
RDF                  0.7832

There is certainly a gap with the management of CBR/ABR. But ADC with the options -tx -q12  I get for example:
Resulting ODG:  -0.88
Resulting DIX:   1.03
BandwidthRef    14253.3514
BandwidthTest   14252.6861
NMR             -13.1225
WinModDiff1     4.6411
ADB             1.3101
EHS             0.2593
AvgModDiff1     3.6089
AvgModDiff2     8.0902
NoiseLoud       0.1116
MFPD            1.0000
RDF             0.0512


ODG (Objective Difference Grade): Measures perceived fidelity, where scores range from 0 (perfect fidelity) to lower negative values indicating increased perceptible quality degradation. A higher (closer to zero) ODG indicates better quality.

DIX (Distortion Index): Represents the total distortion level within the processed audio, with lower values indicating better quality. It's a metric that combines several distortion measures to offer an overall indication of the codec's accuracy.

BandwidthRef and BandwidthTest:

BandwidthRef is the reference (original) signal's bandwidth in Hz, indicating the highest frequency component captured in the original audio.
BandwidthTest is the bandwidth after compression and decompression, showing the highest frequency maintained post-processing. Lower values suggest possible loss of high-frequency information.
NMR (Noise-to-Mask Ratio): Reflects the audibility of noise introduced by compression. A more negative NMR value indicates that the added noise is less perceptible because it’s effectively masked by the audio signal, leading to a cleaner, more faithful reproduction.

WinModDiff1: Represents the windowed difference in signal modulation (amplitude/phase distortion) over short windows, where lower values indicate a more faithful signal with minimal short-term distortion.

ADB (Average Distortion per Band): Measures the average distortion within distinct frequency bands. Lower ADB indicates more accurate reproduction across the audio spectrum.

EHS (Error Harmonic Structure): This parameter measures the harmonic structure of the error or distortion introduced, with lower values suggesting that the distortion is less likely to be perceived as unnatural by listeners.

AvgModDiff1 and AvgModDiff2:

AvgModDiff1 is the average modulation difference over short time scales, indicating how closely the processed signal matches the original in terms of amplitude and phase.
AvgModDiff2 is the long-term version of AvgModDiff1, measuring modulation similarity over longer time windows.
NoiseLoud (Noise Loudness): Measures the perceived loudness of noise introduced by the codec. Lower values indicate that the noise is less noticeable to the human ear, leading to a cleaner sound.

MFPD (Mean Frequency Perceptual Deviation): Measures the perceptual accuracy of high frequencies. A perfect score of 1.0 indicates no deviation from the reference signal in high-frequency perception.

RDF (Relative Delay Factor): Indicates any phase or timing discrepancies between the reference and test signals. Lower values suggest minimal delay, which helps maintain a more natural and cohesive audio reproduction.
I don't give up on what you say. I'm not looking for innovation but a different way to compress audio.


thanks for providing link to EAQUAL will closely inspect it. (The project seems last active 7 years ago)

Also you could try other audio evaluation scores like PSNR SDR SISDR MAE NRMSE MDA all available in librempeg.
Please remove my account from this forum.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #83
All those measurements are irrelevant with perceptual lossy codecs. Only thing that matters is how they sound.

Edit: clarification: All those measurements are *wrong* for perceptual lossy codecs. They don't measure audio the way ear hears things.

Yeah. With hearing I found serious problems with lower (and default q4) presets. Only higher presets can give decent quality but compression is quite poor. No idea if it's okay compared to ADPCM, but at least seems similar (even worse?) than QOA.
This is valid only for version 0.60 since I didn't test 0.70, but I don't expect great improvements at this point.

I think ADC is a lot worse than QOA, even with the last version. This is obvious with that killer sample, also there's no sound at all at the end of Melodi 6. I ABX'ed them and attached the reports below.

The author claims this codec gives superior results for music while it does not at all, and gives no information about the background. The codec creates very weird artifacts, and it's name is also somewhat confusing (there's ADPCM). And, the author does not attach the executable to the post but gives a link to a not well-known website. These are why I thought ADC could be a malware. Also, my computer slowed down after I wrote my previous post in this topic. Does anyone have an idea about that?

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #84
ADC does not target source audio of 8bit PCM
Please remove my account from this forum.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #85
I thank everyone for the tests (except for someone who doesn't deserve respect for the ridiculous comments he makes). For the -b26 option it makes no sense as at minimum it is set to 128 kbps but being an 8 khz sound which is already terrible in quality. I respect the choice of tests which is considerably reductive. In my tests on "Sopranino Recorder Concerto, RV 443_ Allegro" by Vivaldi test file for example with EAQUAL - Evaluation of Audio Quality ( https://github.com/spxnn/eaqual - https://www.rarewares.org/files/others/eaqual.zip ),

mp3 192 kbps  results:
Resulting ODG:  -0.16
Resulting DIX:   2.32
BandwidthRef    17511.4298
BandwidthTest   15909.6910
NMR                 -15.6350
WinModDiff1     5.0334
ADB                   -0.8332
EHS                   0.2262
AvgModDiff1     5.1856
AvgModDiff2     9.0777
NoiseLoud         0.0853
MFPD                  1.0000
RDF             0.0041

while with ADC always at 192 kbps I get this:
Resulting ODG:  -3.05
Resulting DIX:  -1.26
BandwidthRef    11930.2636
BandwidthTest   11913.7601
NMR                  -2.9485
WinModDiff1     12.0720
ADB                  1.8283
EHS                    0.2967
AvgModDiff1     10.4023
AvgModDiff2     26.8317
NoiseLoud        0.3622
MFPD               1.0000
RDF                  0.7832

There is certainly a gap with the management of CBR/ABR. But ADC with the options -tx -q12  I get for example:
Resulting ODG:  -0.88
Resulting DIX:   1.03
BandwidthRef    14253.3514
BandwidthTest   14252.6861
NMR             -13.1225
WinModDiff1     4.6411
ADB             1.3101
EHS             0.2593
AvgModDiff1     3.6089
AvgModDiff2     8.0902
NoiseLoud       0.1116
MFPD            1.0000
RDF             0.0512


ODG (Objective Difference Grade): Measures perceived fidelity, where scores range from 0 (perfect fidelity) to lower negative values indicating increased perceptible quality degradation. A higher (closer to zero) ODG indicates better quality.

DIX (Distortion Index): Represents the total distortion level within the processed audio, with lower values indicating better quality. It's a metric that combines several distortion measures to offer an overall indication of the codec's accuracy.

BandwidthRef and BandwidthTest:

BandwidthRef is the reference (original) signal's bandwidth in Hz, indicating the highest frequency component captured in the original audio.
BandwidthTest is the bandwidth after compression and decompression, showing the highest frequency maintained post-processing. Lower values suggest possible loss of high-frequency information.
NMR (Noise-to-Mask Ratio): Reflects the audibility of noise introduced by compression. A more negative NMR value indicates that the added noise is less perceptible because it’s effectively masked by the audio signal, leading to a cleaner, more faithful reproduction.

WinModDiff1: Represents the windowed difference in signal modulation (amplitude/phase distortion) over short windows, where lower values indicate a more faithful signal with minimal short-term distortion.

ADB (Average Distortion per Band): Measures the average distortion within distinct frequency bands. Lower ADB indicates more accurate reproduction across the audio spectrum.

EHS (Error Harmonic Structure): This parameter measures the harmonic structure of the error or distortion introduced, with lower values suggesting that the distortion is less likely to be perceived as unnatural by listeners.

AvgModDiff1 and AvgModDiff2:

AvgModDiff1 is the average modulation difference over short time scales, indicating how closely the processed signal matches the original in terms of amplitude and phase.
AvgModDiff2 is the long-term version of AvgModDiff1, measuring modulation similarity over longer time windows.
NoiseLoud (Noise Loudness): Measures the perceived loudness of noise introduced by the codec. Lower values indicate that the noise is less noticeable to the human ear, leading to a cleaner sound.

MFPD (Mean Frequency Perceptual Deviation): Measures the perceptual accuracy of high frequencies. A perfect score of 1.0 indicates no deviation from the reference signal in high-frequency perception.

RDF (Relative Delay Factor): Indicates any phase or timing discrepancies between the reference and test signals. Lower values suggest minimal delay, which helps maintain a more natural and cohesive audio reproduction.
I don't give up on what you say. I'm not looking for innovation but a different way to compress audio.


thanks for providing link to EAQUAL will closely inspect it. (The project seems last active 7 years ago)

Also you could try other audio evaluation scores like PSNR SDR SISDR MAE NRMSE MDA all available in librempeg.
Thank you very much. I'm glad you explained that ADC currently focuses on a 16-bit stereo format. He also finds it difficult to understand that he is experimental. I'm doing some tests using FFT also just to understand better. Compression is better at low bitrates but worse at high bitrates. If you are interested I can include the possibility of using the frequency domain you do not have levels of other codecs only as a transformation.  


I don't care about QOA which is studied in depth as code. He does a really good job. However, it is limited to 8 maximum values ​​while ADC uses from 3 to 32 values ​​and not bits.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #86
The problem is that you use this EAQUAL metrics  from github project that is abandoned and extremely obscure.
So any claims that you try to backup with that results from that tool can be easily rejected.
Please remove my account from this forum.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #87
I managed to find an exe version of PQevalAudio v3r0. I retested the wav file I mentioned at 48 khz and obtained these results which confirm what you said, I don't know if in part.

MP3 constant 192 kbps 48 khz results :
Model Output Variables:
   BandwidthRefB: 721.319
  BandwidthTestB: 665.549
      Total NMRB: -15.4426
    WinModDiff1B: 5.50865
            ADBB: -0.664927
            EHSB: 0.461547
    AvgModDiff1B: 5.67492
    AvgModDiff2B: 9.55488
   RmsNoiseLoudB: 0.0956279
           MFPDB: 0.978912
  RelDistFramesB: 0.00756259
Distortion Index: 2.191
Objective Difference Grade: -0.202

ADC -tx -q8 option: 265 kbps

Model Output Variables:
   BandwidthRefB: 542.998
  BandwidthTestB: 542.98
      Total NMRB: -10.4733
    WinModDiff1B: 6.32794
            ADBB: 1.37051
            EHSB: 0.50724
    AvgModDiff1B: 5.13273
    AvgModDiff2B: 11.114
   RmsNoiseLoudB: 0.166043
           MFPDB: 0.999882
  RelDistFramesB: 0.148557
Distortion Index: 0.329
Objective Difference Grade: -1.538

ADC -tx -q12 option:  314 kbps

   BandwidthRefB: 596.714
  BandwidthTestB: 596.714
      Total NMRB: -14.2247
    WinModDiff1B: 4.34681
            ADBB: 1.2962
            EHSB: 0.493075
    AvgModDiff1B: 3.26773
    AvgModDiff2B: 6.82411
   RmsNoiseLoudB: 0.108159
           MFPDB: 0.997369
  RelDistFramesB: 0.0356398
Distortion Index: 1.156
Objective Difference Grade: -0.786


ADC -tx -b192 option:

Model Output Variables:
   BandwidthRefB: 481.05
  BandwidthTestB: 480.706
      Total NMRB: -2.86482
    WinModDiff1B: 12.6897
            ADBB: 1.85299
            EHSB: 0.597898
    AvgModDiff1B: 10.9897
    AvgModDiff2B: 26.7369
   RmsNoiseLoudB: 0.394353
           MFPDB: 1
  RelDistFramesB: 0.825582
Distortion Index: -1.335
Objective Difference Grade: -3.105

Below is the explanation that ChatGPT provided me with the ideal values:

Metric   Value   Ideal Value Range   Problematic Value Range   Interpretation
BandwidthRefB         > 500 Hz            < 500 Hz     Wide reference bandwidth is positive for audio quality.
BandwidthTestB      > 500 Hz            < 500 Hz   If it differs significantly from BandwidthRefB, it may indicate frequency loss in the test file.
Total NMRB               < -5                          > 0               Negative values mean noise is masked, indicating good quality.
WinModDiff1B      < 5                           > 10      Lower modulation difference means better similarity between files.
ADBB                     < 1.5                                   > 3           Low distortion across bandwidth is preferable.
EHSB                     < 0.5                                   > 1           Lower values indicate minimal harmonic distortions.
AvgModDiff1B        < 5                      > 10   Small modulation differences suggest high fidelity to the original.
AvgModDiff2B      < 5                         > 10   Lower differences in high-frequency modulation improve quality.
RmsNoiseLoudB                 < 0.5                  > 1   Low values indicate an acceptable noise level.
MFPDB                            < 2                           > 5   Low frame distortion indicates similarity between files.
RelDistFramesB                 < 0.5                          > 1   Low percentage of distorted frames represents good overall quality.
Distortion Index               < 0.5                   > 1   Lower index indicates lower distortion; high values suggest degradation in the test file.
Objective Difference Grade   > -1                        < -3   Values close to zero are better; highly negative values indicate noticeable differences.

In these terms MP3 is terrible in terms of distortion!!!! :))  :))  :))  :))  :))  8)

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #88
I managed to find an exe version of PQevalAudio v3r0. I retested the wav file I mentioned at 48 khz and obtained these results which confirm what you said, I don't know if in part.

Why do you keep using an algorithm to determine the quality? It's wrong, and MP3 is totally transparent to most people starting from 128kbps at worst (at [any sampling rate] stereo) while ADC is not even at 181kbps as I proved.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #89
If you are a C++ programmer, download mp3 lame and see how many dozens of filters there are to extrapolate and cut. purify and clean up the original sound which will obviously be artificial and artificial. A summary. Needless to say, most codecs produce artificial, high-quality clipped sound. Simple. (This is my personal opinion and not a fact.)

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #90
If you are a C++ programmer, download mp3 lame and see how many dozens of filters there are to extrapolate and cut. purify and clean up the original sound which will obviously be artificial and artificial. A summary. Needless to say, most codecs produce artificial, high-quality clipped sound. Simple.

You can prefer ADC's sound color (I don't), but this does not change the fact that MP3 reaches transparency at a much lower bitrate than ADC does. You're also violating TOS#8.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #91
I checked again and the "Distortion Index" values ​​are to be considered the opposite of what was said before!

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #92
[quote
You can prefer ADC's sound color (I don't), but this does not change the fact that MP3 reaches transparency at a much lower bitrate than ADC does. You're also violating TOS#8.
[/quote] This is currently a given. But that's not why I say I'm closing everything and letting it go. I try to improve. Mp3 can't improve.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #93
The problem is not the age of EAQUAL. Programs that supposedly measure objective audio quality are not comparable to how actual human hearing works. Some try to mimic hearing, but none of them do it correctly.
When comparing audio quality only actual human listener can say which one sounds closer to the original. And all the people replying to you with listening results say that ADC doesn't perform as you claim or hope.

It seems that audio moderation is dead on this forum after some long time admins and mods have disappeared. Korth is active but on different area. All your claims violate the TOS8 forum rule. I'm not often defending the rule but in this instance it's very important, as some lazy readers may actually think that ADC beats long established codecs in quality.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #94
Said like that, it could be fine. But conside.: So I should present ADC as an example. "I'm working on a new codec that doesn't use the frequency domain. But don't try it, there are other better codecs!"

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #95
You can say you think it sounds good, and you can give examples where you think it sounds better than MP3. But you can't make claims that it's better than something else based on results from those tools you have used before.

If you want to produce numbers about quality, you can use ABC/HR to do double blind listening tests and post the results from those. Best would be if you would get multiple listeners to participate.

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #96
I have never said that I sound better than mp3 or other codecs, but that it does not currently use filters like other frequency domain codecs, and in my opinion, not using filters, for me and only for me is a better way to hear nearby sounds to the original! point ! If you don't care about the codec and think I'm naive, don't write then!
If you consider for example H264 or other video codecs they are the best, yet someone is working on video codecs based on wavelet coding. They are driven by what, the belief that DCT is superior? I do not believe ! that's why we have to attack them. I see them as fantastic researchers of a different way. 

Maybe you don't know it but I created well-known data compression programs such as ZCM which is still unique in its compression sector! I have always gone against the current to look for something new!

One last thing. Here we are in the "Other Lossy Codecs" section. What are we talking about, you know we are in a secondary or tertiary section. I didn't put my codec in the stable and famous codecs!

 

Re: ADC (Adaptive Differential Coding) My Experimental Lossy Audio Codec

Reply #97
From above results its shows for 192kbps that "objective difference grade" is relatively worse when compared to mp3. While for same bitrate mp3 have extremely low score which is considered better, maybe that points out that it is easily ABXed when compared to mp3 coding.
Please remove my account from this forum.