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To get into the functional programming side, I’m learning more and more about a functional music package in Haskell: harmtrace. It can parse a chord sequence (what I’m using it for), and do much more music analysis in a clean and functional way.
Thanks to the help of the authors of this package, I was finally able to run it using the binary. (Still not able to build it though, because of all the version issues with ghc..)
Some specifics are given here:
Here’s the screen shot of running it in terminal:
The output is a php syntax tree like this:
To visualise it, one can use this website:
And the visualisation looks like this:
In the future, more on the analysis of these trees…
which means Asia for me in October and maybe November!
Paper title: A comparison and fusion of musical pattern discovery
algorithms (Paper #120) -> Finding the consensus among musical pattern discovery algorithms (after first revision) -> ???
It was a bumpy road towards submission: realising the overall results are not good enough and you have to write an almost completely new paper with new dataset, new algorithms and new results in less than two weeks… It was an intensive working schedule towards the deadline. But I didn’t hate it. I should have know better though…
The happiness of getting accepted is now mixed with the not-so-fun process of revision. This step is mostly small things, but still important: make the figures and text clearer, make the contribution and purpose of the paper more obvious, etc. One pain is to re-generate the figures which need to be improved. Because of all the deadline hassle, I didn’t really comment my code well. To get back to my own thinking 2-3 months ago was amazingly hard!
Finally, I think I’m starting to like writing and reading papers more. It’s a old way of communication but one can convey and grasp all the info if they really try..
Since I got the idea that quickcheck can be used to generate things, I wanted to use it for something about music. I found by this post: http://chromaticleaves.com/posts/generate-user-data-quickcheck.html and it seems to be a good starting point.
I just did something very easy to change the codes, but I think it’s quite a nice learning experience for Haskell beginners like me.
The output is a tuple with the root note and the chord quality. There hasn’t been any restriction implemented in this so the chord sequence doesn’t really make sense musically. Something to play with in the future!
So satisfying when you ghci it and it just works!!
This is a try to run the tensorflow functionalities (https://github.com/tensorflow/haskell) under Ubuntu.
Basically I just followed the instruction on the github page. I heard people have had bad experience with it, but it’s been pretty smooth for me. There’s indeed something tricky if you haven’t installed docker. But it’s pretty easy to fix, just follow the instruction given by the system.
Some screen shots after successfully testing the system:
The MNIST task: good guess!
June is the month of festivals in the Netherlands it seems!
Although it’s been quite a while, here are some pics from Red Light Jazz festival and Japan market:
There are so many more and each one of them has something unique 😀
Another event recommended by a friend is the Spring Utrecht. It happened even earlier. I was lucky enough to be in one of the rehearsals for one of the shows. It was very interestingly about sound and movement: using your body and movement to create different sound effects in an empty space. I definitely felt the pro-ness from the leader. But I didn’t have the time to more rehearsals and to the shows, unfortunately…
I just discovered that they are actually doing more of it:
Spring in Autumn
Maybe worth a look!
Thanks to a master student studying at Eindhoven, I got the chance to play with a music pattern visualiser. You can find his repo here: https://github.com/Shiroid/Thesis-Pattern-Discovery-In-Families/tree/master/Builds
The work is mostly based on Peter Boot’s paper:
Boot, Peter, Anja Volk, and W. Bas de Haas. “Evaluating the Role of Repeated Patterns in Folk Song Classification and Compression.” Journal of New Music Research 45.3 (2016): 223-238.
Using this, we are able to see what are the patterns found by various pattern extraction algorithms. In addition, we can also see the differences using different parameters of the algorithms. There’s another option where you can compare the patterns across a whole tune family.
Some screen shots are here:
As written in this post, I also tried to visualise the algorithmically extracted music patterns. My focus was more on the comparison amongst algorithms and the location of the patterns.
This program provides more in terms of the comparison amongst different parameters and across the whole tune families. It would also be nice if the users would be able to export some statistics of the visualisation. The author said it’s possible but not a priority yet…
Looking forward to his thesis! Keep the good work 🙂
First animecon in the Netherlands. The size is not as the one in Paris but still a pretty decent and cosy size. This time I couldn’t make it to the over-night sessions, but maybe next year, it looks fun!
My targets were originally the workshops and karaoke. It was nice to talk to people in the venue, too. A happy surprise was to see music improvisation at the venue. It’s just a good place to make some connections with people sharing some same interests.