Results

Qualitative Results

Note that only the guitar track is shown.

Strategy	Result
raw prediction of the pretrained G
Bernoulli sampling (at test time)
hard thresholding (at test time)
proposed model with SBNs
proposed model with DBNs

Quantitative Results

Evaluation metrics

Qualified note rate (QN) computes the ratio of the number of the qualified notes (notes no shorter than three time steps, i.e., a 32th note) to the total number of notes. Low QN implies overly fragmented music.
Polyphonicity (PP) is defined as the ratio of the number of time steps where more than two pitches are played to the total number of time steps.
Tonal distance (TD) measures the distance between the chroma features (one for each beat) of a pair of tracks in the tonal space proposed in [1].

Comparisons of training and binarization strategies

two-stage_polyphonicity

two-stage_qualified_note_rate

end2end_qualified_note_rate

Effects of the shared/private and multi-stream design of the discriminator

ablated_qualified_note_rate

ablated_tonal_distance

Audio Samples

The audio samples presented below are in a high temporal resolution of 24 time steps per beat. Hence, they are not directly comparable to the results presented on the MuseGAN website.

No cherry-picking. Some might sound unpleasant. Lower the volume first!

Model	Result
hard thresholding (at test time)
Bernoulli sampling (at test time)
proposed model (+SBNs)
proposed model (+DBNs)
end-to-end model (+SBNs)
end-to-end model (+DBNs)

Reference

Christopher Harte, Mark Sandler, and Martin Gasser, “Detecting Harmonic Change In Musical Audio,” in Proc. ACM MM Workshop on Audio and Music Computing Multimedia, 2006.