cpd73 wrote: 
> 
> I'm wondering, seeing as I only really care about similarity, whether I
> could just use the low-level results - and compare (a selection of)
> these against files to get a similarity. I'm saving the raw JSON output
> from the high-level analysis, so trying with low level analysis will not
> need a complete re-scan. I just need to decide which of the values to
> use...
That may be more involved than you'd expect.
- first, you'd need to identify the audio features suited to this task
(see 'A Review of Physical and Perceptual Feature Extraction Techniques
for Speech, Music and Environmental Sounds'
(https://www.mdpi.com/2076-3417/6/5/143/htm) for an overview, and 'this
page' (https://essentia.upf.edu/streaming_extractor_music.html) for
essentia_streaming_extractor_music's capabilities)
- then, you'd find a way to compute the similarity for each feature
(e.g. musly uses the Kullback-Leibler divergence for MFCCs)
- finally, you'd have to combine the similarity of all features and find
a way to compare songs

Note that if you use essentia_streaming_extractor_music, you'd also have
to configure it to store all frame values (by default, only the
statistics computed over frames are included in the output). At this
point, using Essentia's API directly would make more sense.



'Various SW' (https://www.nexus0.net/pub/sw/): Web Interface | TUI |
Playlist Editor / Generator | Music Classification | Similar Music |
Announce | EventTrigger | Chiptunes | LMSlib2go | ...
'Various HowTos' (https://www.nexus0.net/pub/documents/LMS/): build a
self-contained LMS | Bluetooth/ALSA | Control LMS with any device | ...
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