It is used to calculate MEI 20190207, the lower the Dissonance, the higher the MEI 20190207. LANDR is probably impossible to avoid because there is no such setting.ĭissonance is an index to measure dissonance degree. If you set Ceiling to True Peak in AI Mastering, you can prevent True Peak from exceeding 0 dB, so you can avoid degrading sound quality. If True Peak is larger than 0 dB, it may be distorted due to re-encoding etc, but there seem to be cases where both AI Mastering and LANDR exceed 0 dB.

True Peak (inter sample peak) is an average of all songs. In general, the loudness and the loudness range are in a trade-off relationship, but the decrease in the loudness range when AI Mastering has a higher loudness than LANDR is small. I plotted the average of all songs in loudness and the average of all songs in loudness with a scatter plot. AI Mastering tends to have higher MEI 20190207 than LANDR. It is the average of MEI 20190207 change with respect to the original for all songs. Comparison result Change amount of MEI 20190207 Loudness range, True Peak Mastering setting If the sound quality is the same, the loudness should be large. It sounds better as you play with loud sounds. Depending on the platform to be delivered and how the user listens, it is highly likely that songs with loudness are more likely to be played with louder sounds as compared to other songs. It is the loudness defined by ITU-R BS.1770. The mixed audio used for weight learning is all the mixed audio that is published in MixBrowser, with preview audio.

Simply put, I calculate it based on the shape of the spectrum, the dynamic range, the spread of space, the bandwidth of the attack, and the amount of distortion. The original indices are the spread covariance matrix of the spectrum, the mean of the spectrum, Hardness, Dissonance. MEI 20190207 is calculated by the weighted sum of various indices. It is the main indicator in this comparison. It is intended for comprehensive evaluation. It is an evaluation index of mixed audio, but I think that it can also be used for evaluating mastering audio. Mi圎valuationIndex 20190207 (MEI 20190207) is an objective evaluation index of mixed audio constructed using subjective evaluation data of The Mix Evaluation Dataset. THE MIX EVALUATION DATASET index Mi圎valuationIndex20190207 (MEI20190207) Please see the GitHub repository below for a specific mix list. The reason is that it is easy to master without artifacts when the loudness range is large, and there is a mismatch of automatic mastering when the subjective evaluation is low. In the mix audio license, CC BY's, we selected the one with the largest loudness range for each song and the one with the lowest average subjective rating as the comparison target tone. This mix evaluation data set includes multiple mixed audio for various songs and subjective evaluation results by multiple people for each mixed audio. We chose the sound to be compared from the following mix evaluation data set. Mastering various sounds with LANDR and AI Mastering and comparing the results with various indicators. * Since there are comparative sounds in the other people, please listen Comparison method We found that AI Mastering has higher MEI 20190207 than LANDR.ĪI Mastering has a tendency that the loudness range is larger than the LANDR, the Boominess is small, the Depth is small, and the Warmth is small.

We compared the sounds mastering with AI Mastering and LANDR at MEI 20190207. We proposed an index that can objectively evaluate the mix MEI 20190207.

Landr mastering