Comments (9)
-
i would love to see a post about
waveplot
and how it keeps a low memory usage. The email to John Davis from a few days ago (copy-pasted with permission on this StackOverflow board) could be used as a starting point: https://stackoverflow.com/questions/57260065/why-does-librosa-plot-differ-from-matplotlib-and-audacity -
as i wrote earlier on the Slack channel,
librosa.util.valid_audio
is one of my most cherished yet under-appreciated librosa features. I would be in favor of giving it more publicity :) we could write a short post about that.
from blog.
We should probably do a comprehensive post about all the various efficiency improvements in the 0.10 release.
from blog.
@lostanlen I also drafted up a post on block streaming, care to give it a looksy before I publish?
from blog.
Maybe also a plot on all the bells and whistles of specshow
, compared to (say) imshow.
from blog.
Yes, specshow
is a major feature in librosa, and some uses are not trivial. For example:
- Explaining how the color map gets assigned (
magma
vs diverging) + a cautionary word againstjet
? - How to make sure that the axis ticks show physical units, not frame indices (one of my biggest pet peeve as a reviewer!).
- How to make sure that the contrast is right.
- How to have several spectrograms share the same colormap and the same axes
- How to make the y-axis in CQT specshow be scientific pitch
- How to annotate a spectrogram with
piptrack
- How to annotate a spectrogram with
beat_track
This covers probably more than one post, but it's all very relevant IMO.
from blog.
SGTM in general! I'm not sure what exactly you have in mind for piptrack
, can you elaborate?
from blog.
What i mean is to have a pitch curve (or spectral centroid, or whatever frequency-valued signal) overlayed on top of the CQT
from blog.
Post ideas to accompany the 0.7.1 release:
- framing
- feature inversion (incl cqt griffin-lim)
- replicating HTK features
- pitch tracking and plotting?
from blog.
replicating HTK features
Yes. I think that the big take-home message here is that there is no such thing as "the MFCC" of a signal. It all depends on what well-established implementation we're trying to replicate, which ultimately falls back on which psychometric study we're relying on for the mel scale.
This (under-cited) paper about "fitting the mel scale" was a big eye-opener for me in this regard:
https://ieeexplore.ieee.org/document/758101
Pitch tracking and plotting: yes! will submit a WIP PR tonight.
from blog.
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