David Mandelberg https://david.mandelberg.org Freelance cyber security consultant, software developer, and more. Sat, 12 May 2018 00:41:34 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.6 https://david.mandelberg.org/wp-content/uploads/2017/09/cropped-P1230630-raw-crop-square-full-32x32.jpg David Mandelberg https://david.mandelberg.org 32 32 Sheep Photos https://david.mandelberg.org/2018/05/12/sheep-photos/ https://david.mandelberg.org/2018/05/12/sheep-photos/#respond Sat, 12 May 2018 00:41:34 +0000 https://david.mandelberg.org/?p=3057 ]]> https://david.mandelberg.org/2018/05/12/sheep-photos/feed/ 0 Blizzard Sledding, Skiing, and Kayaking https://david.mandelberg.org/2018/03/18/blizzard-sledding-skiing-and-kayaking/ https://david.mandelberg.org/2018/03/18/blizzard-sledding-skiing-and-kayaking/#respond Sun, 18 Mar 2018 02:18:35 +0000 https://david.mandelberg.org/?p=3013 Earlier this week, I ventured into a beautiful blizzard with a friend to go sledding and skiing at President’s Lawn, Tufts University. Here are the resulting video and photos, including shots of the amazing Tufts Ski Team:

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Cryptography, Dancing, Morse Code, Number Theory, and Music https://david.mandelberg.org/2018/03/13/cryptography-dancing-morse-code-number-theory-and-music/ https://david.mandelberg.org/2018/03/13/cryptography-dancing-morse-code-number-theory-and-music/#respond Tue, 13 Mar 2018 23:27:23 +0000 https://david.mandelberg.org/?p=3005 What do cryptography, dancing, Morse code, number theory, and music have in common? My latest album: Sweet Suites, Volume 1: Um… What?

album art, from top to bottom: "Sweet Suites, Volume 1: Um… What?" / "David Mandelberg" / picture of a geode / "Cipher Suite no. 1 “Deprecated”" / "Morse Code Suite no. 1" / "Piano Axioms Suite no. 1" "Morse Code Suite no. 1 for Solo Vuvuzela"
Cover art for Sweet Suites, Volume 1: Um… What?

Cipher Suite no. 1, Fs PSK_PBKDF2_SNOW_HMAC, “Deprecated” (music video, sheet music) is my attempt to turn a cipher suite into a suite of dance music based on the cryptographic algorithms. In Pavane for a Pre‐Shared Key, Alice (clarinet) and Bob (violin) are in perfect sync throughout a slow and formal key agreement (dance). For the Password‐Based Key Derivation Function Two‐Step, cryptographic key derivation is represented by frequent musical key changes. Sometimes Alice derives new keys from a secret; sometimes Bob does; sometimes they both derive the same keys from the same secret. Once data encryption key(s) are available, Alice and Bob can start sending encrypted messages using a stream cipher, in Snoa in the SNOW. As they go through the ciphertexts in this dance music, they frequently lose synchronization, but they recover each time. Finally, they authenticate their messages with a Hash‐Based Message Authentication Zwiefacher. The zwiefacher’s formula is (PPWWP)2: initialize inner hash (pivot), XOR with inner pad (pivot), update inner hash with K′ XOR inner pad (waltz), update inner hash with message (waltz), finalize inner hash (pivot), initialize outer hash (pivot), XOR with outer pad (pivot), update outer hash with K′ XOR outer pad (waltz), update outer hash with inner hash result (waltz), finalize outer hash (pivot).

Morse Code Suite no. 1, Fs 1865 (music video, sheet music) comes from my realization a while ago that I really like the sound of International Morse Code’s rhythm, and my inability to find any music with that rhythm. (There is plenty of music that incorporates Morse code, but I didn’t find any that used standard timings for a significant portion of the tune.)

Piano Axioms Suite no. 1, Fs ℕ (music video, sheet music) exists because I saw an unfulfilled mathematical pun opportunity in the name of the Peano axioms (a.k.a., Peano postulates). In each of the five axioms/postulates/movements, rests represent zero and successive notes represent successive natural numbers.

Finally, because vuvuzelas amuse me, I arranged Morse Code Suite no. 1 for Solo Vuvuzela, Fs 1865‽ (music video, sheet music). It sounds pretty bad, but that’s definitely the point.

Get the album today (or tomorrow, or not at all, who am I to tell you what to do?) on Bandcamp.

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Inbreeding, Time Travel, and Graph Theory https://david.mandelberg.org/2018/01/27/inbreeding-time-travel-and-graph-theory/ https://david.mandelberg.org/2018/01/27/inbreeding-time-travel-and-graph-theory/#comments Sat, 27 Jan 2018 02:34:49 +0000 https://david.mandelberg.org/?p=2971 While working on livestock management software for a client, I got to thinking. How much harder would inbreeding calculations be, if an organism could travel back in time to be its own ancestor? Disclaimer: this has not been peer reviewed, let alone reviewed by anybody with more than a high school level understanding of biology or time travel.

First, let’s start with an incredibly degenerate case. Alice takes her son Bob on a vacation into the future. While then, Bob picks a pretty flower and hides it in his pocket. He names the flower Carol. Upon returning to their native time, Bob immediately runs outside and replants the flower. Some time later, the flower fertilizes itself and produces an offspring, which is later picked up by young Bob.

graph with 3 "Carol" nodes, and arrows from each of two to the third
Carol’s pedigree

In this case, Carol contributed both of the haploids that merged to form herself. She’s her own parent, twice over. Each of Carol’s homozygous loci has a 100% chance of producing identical alleles in the gametes, and therefore the same homozygous locus in the offspring (which is also Carol). Each of Carol’s heterozygous loci has a 50% chance of giving the same allele to the male gamete as what was in the male gamete that produced Carol; similarly and independently, it has a 50% chance of giving the correct allele to the female gamete. Combined, there’s a 25% chance that a single heterozygous locus will result in the same genetic path that produced itself. However, unlike with normal inbreeding calculations, we know that all the genes of Carol as a child are equal to Carol as the parent. Therefore, let n be the number of loci, and the probability of heterozygosity due to descent is 0.25n. The probability of homozygosity due to descent, i.e., the coefficient of inbreeding, is therefore 1 − 0.25n. Luckily, Alice is a botanist, so when she discovers what Bob did, she teaches her son an interesting lesson about genetics and time travel.

ram ignoring food trough to look at the camera
Fred, the very attractive ram

Elsewhere in the world, Dave is a sheep farmer who’s about to go on a business trip to a few years in the past. Unfortunately, things don’t go according to plan, when his prized ewe Eve sees the portable time machine and thinks it’s a bucket of corn. She bumps into Dave, who was already nervous about time travel. He fumbles the time machine, which falls on Eve and activates. Dave spends the rest of the day talking to insurance companies. Meanwhile in the past, Eve meets a very attractive ram named Fred.

pedigree graph showing Eve descended from herself
Eve’s pedigree

Since this is theory instead of reality, let’s ignore what actually happens next, and instead generalize and assume. Two of Eve’s ancestors are a mated couple, herself and Fred. Without looping, there are n generations from Eve as an ancestor to Eve as a descendant. I.e., n=1 represents Eve as her own parent, n=2 represents Eve as her own grandparent but not her own parent, etc. To make things easier, assume there are no other common ancestors, so that every ancestor of Eve that is not also a descendant of Eve has a coefficient of inbreeding of 0. Tracing genetic paths from Eve0 back n generations gives 2n distinct genetic paths, one of which is to Eve1 herself. Thus, each locus has a probability of 2n+1 of having an allele passed down from Eve1 to Eve0. For each of those loci, if Eve1 is homozygous at the locus, she’ll pass down the correct allele (the one she got from herself, Eve2). If Eve1 is heterozygous at that locus, there’s a 50% chance she’ll pass down the correct allele. As in the degenerate case, we know that all of the genes that are passed down to herself are the same ones received from herself. So let m be the total number of loci, and the expected number of loci with alleles Eve passes to herself is 2n+1m. Therefore, the probability of heterozygosity at those loci is 0.5(2n+1m). The other loci have alleles from unrelated ancestors, so Eve’s total probability of homozygosity is 2n+1(1 − 0.5(2n+1m)). Except for small values of n, that’s really not bad at all!

Generalizing these cases into a comprehensive algorithm for calculating inbreeding in the face of time travel is left as an exercise for the reader. But I suspect it involves a multidigraph where each vertex represents an individual organism, and each arrow represents a gamete, pointing from the parent that created the gamete to the child created from the gamete. Then that type of graph can be split into cases, with some subgraphs analyzed separately. I think that would probably give an algorithm that’s a hybrid between the above cases and normal inbreeding calculations, but I’m not sure.

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Bailey at Nod Brook https://david.mandelberg.org/2017/11/29/bailey-at-nod-brook/ https://david.mandelberg.org/2017/11/29/bailey-at-nod-brook/#respond Wed, 29 Nov 2017 03:06:27 +0000 https://david.mandelberg.org/?p=2949 ]]> https://david.mandelberg.org/2017/11/29/bailey-at-nod-brook/feed/ 0 Waves of Sin https://david.mandelberg.org/2017/11/28/waves-of-sin/ https://david.mandelberg.org/2017/11/28/waves-of-sin/#respond Tue, 28 Nov 2017 18:21:47 +0000 https://david.mandelberg.org/?p=2939 What do you get when you combine a pseudo‐random number generator, the sine function, and some C++ code? In this case, an album of very strange music. With a POSIX shell script and ffmpeg thrown into the mix, you also get music videos.

graph paper with "Waves of Sin" written using mostly sine waves for letters, and "David Mandelberg" written by hand with a pencil
Cover art for Waves of Sin

The album opens with Signals of Sin and closes with Signals of Sin (reprise), because of course music needs telephony signals to frame it. (These are the only two tracks that are not pseudo‐randomly generated.)

Tracks 2–10 explore what happens when you use a pseudo‐random number generator to pick the number of simultaneous “notes,” and the duration, pitch, volume, and left–right pan of each note. To create variety, some tracks (e.g., Sparse Waves of Sin) have very few simultaneous notes, while others (Way Too Many Waves of Sin) have… more. Some tracks have normal‐length notes; Super Fast Waves of Sin and Hyper Fast Waves of Sin don’t. Some tracks include harmonics (e.g., Harmonic Waves of Sin), others have only fundamentals. And for the strangest tracks (Interfering Waves of Sin and Harmonic Interfering Waves of Sin), each note is represented by a spread of interfering frequencies, instead of a single fundamental frequency and optional harmonics.

Finally, the album would not be complete without the raw output of its pseudo‐random number generator, i.e., some white noise: Dedication to Mersenne Twister 19937, Without Which This Album Would Have Been Slightly Different.

I’m definitely not claiming that this is my new favorite form of music, or even that it’s particularly consonant, but after playing around with the code and parameters a bunch, I grew to actually enjoy this music. Unlike my previous album. That one just started to grate on me more and more.

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Functional Video Generation https://david.mandelberg.org/2017/11/21/functional-video-generation/ https://david.mandelberg.org/2017/11/21/functional-video-generation/#respond Tue, 21 Nov 2017 20:01:41 +0000 https://david.mandelberg.org/?p=2925 Back in 2011–2012, I played around with generating static images from mathematical functions. Each function effectively took an (x,y) coordinate and returned an RGB tuple. (By mathematical functions, I mean deterministic functions that don’t rely on external input and have no side effects. I.e., given the same input parameters, the function will always return the same value, and do nothing other than return that value.) Some scaffolding code called the function repeatedly and performed anti‐aliasing to produce an image. It was fun to see what I could do just by mapping spatial coordinates to color values.

zone plate with blurry colors in the background black circles of mass, surrounded by colors to indicate the gravity field highly-saturated bright contour lines on a black background

Then earlier this year, I decided to add a time coordinate and make abstract, ambient videos using the same technique. The single‐threaded python code I used for still images was too slow to be practical for long videos, so I started from scratch with new C++ code and an improved interface. The video scaffolding code exposes the below interface for subclasses to define what the video will look like. (The use of ThreadState and TimeState does make the functional abstraction a bit less pure, but it’s important for performance to not re‐do some calculations for every sub‐pixel.) Once a subclass gives a function that defines what the video looks like in theory, the scaffolding code handles anti‐aliasing, motion blur, and rendering to turn it into a finite video that a computer can display.

// Main class to generate a video (or still frame). Subclass this. Use
// ThreadState for any information local to a thread, and TimeState for
// anything local to a single point in time. (There could be multiple
// TimeStates per frame if temporal oversampling is used.)
template <typename ThreadState = NullState, typename TimeState = NullState>
class VideoGenerator : public VideoGeneratorInterface {
…
 protected:
  // Get the color value at a single point in space and time. (x,y) are spatial
  // coordinates, with the smaller dimension in the range [-1,1]. For a 2:1
  // aspect ratio, x would be in the range [-2,2] and y in [-1,1]; for 1:2, x
  // would be in [-1,1] and y in [-2,2]. t is in seconds.
  virtual Rgb PointValue(
      const ThreadState* thread_state, const TimeState* time_state,
      float x, float y, double t) = 0;

  // Override this if the per-thread state shouldn't be null.
  virtual ::std::unique_ptr<ThreadState> GetThreadState() {
    return nullptr;
  }

  // Override this if the per-point-in-time state shouldn't be null.
  virtual ::std::unique_ptr<TimeState> GetTimeState(
      const ThreadState* thread_state, double t) {
    return nullptr;
  }
…
};

The first video I made was directly inspired by the last still image I’d made with the technique, and used a very similar function. For each time value t, three dimensional Perlin noise provides a map from (x,y,t) to a value that I used as the elevation of the (x,y) point on a topographic map. The elevation values are then used to make contour lines with hue denoting the elevation of the line and lightness denoting how close each point is to its nearest contour line. The code is only 43 lines long including boilerplate, and produces this 12 hour long video of gently moving colorful curves:

Next, I played around with interference patterns similar to moiré patterns, to try to generate something even more abstract than an abstracted topographic map. This code uses a set of overlapping, moving blinds to generate patterns of light and dark. The blinds use Perlin noise to independently vary their size and rotation, and to move side to side. Separately, the hue for the entire screen varies over time. Warning: the end result might cause motion sickness in some people. I tried my best to avoid it, but I’m not sure how well I succeeded.

So far, I’m finding the results of functional video generation interesting, though I do think that more traditional computer animation is a lot more versatile.

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Exponential Vuvuzelas Release https://david.mandelberg.org/2017/10/13/exponential-vuvuzelas-release/ https://david.mandelberg.org/2017/10/13/exponential-vuvuzelas-release/#comments Fri, 13 Oct 2017 04:36:26 +0000 https://david.mandelberg.org/?p=2909 If you’re the type of person who always felt that your music collection just needed a few (hundred) more vuvuzelas, then today, you are in luck! Presenting a complete recording of Exponential Vuvuzelas, available for audio download and music video streaming today!

Image of many vuvuzelas in an exponential pattern, with title "Exponential Vuvuzelas" by David Mandelberg. Stickers on the image read: "Now featuring more vuvuzelas than you ever wanted to hear in your entire life!" / "The perfect gift for a friend you don’t like!" / "For best results, pair this quality recording with an even higher quality pair of noise‐reduction ear plugs."
Cover art for Exponential Vuvuzelas
  1. Exponential Vuvuzelas: Act 1, Crescendo: N. 1 Vuvuzela
  2. Exponential Vuvuzelas: Act 1, Crescendo: I. 2 Vuvuzelas
  3. Exponential Vuvuzelas: Act 1, Crescendo: II. 4 Vuvuzelas
  4. Exponential Vuvuzelas: Act 1, Crescendo: III. 8 Vuvuzelas
  5. Exponential Vuvuzelas: Act 1, Crescendo: IV. 16 Vuvuzelas
  6. Exponential Vuvuzelas: Act 1, Crescendo: V. 32 Vuvuzelas
  7. Exponential Vuvuzelas: Act 1, Crescendo: VI. 64 Vuvuzelas
  8. Exponential Vuvuzelas: Act 1, Crescendo: VII. 128 Vuvuzelas
  9. Exponential Vuvuzelas: Act 1, Crescendo: VIII. 256 Vuvuzelas
  10. Exponential Vuvuzelas: Act 1, Crescendo: IX. 512 Vuvuzelas
  11. Exponential Vuvuzelas: Act 1, Crescendo: X. 1024 Vuvuzelas
  12. Exponential Vuvuzelas: Act 2, Diminuendo: I. 1024–0 Vuvuzelas: “Outro”
  13. Exponential Vuvuzelas: Act 2, Diminuendo: N. 0 Vuvuzelas: “A much needed break for your ears”
  14. Bonus! All 37 Samples From Exponential Vuvuzelas, for Your Listening Agony

In addition to the music and videos, there’s also a score of the composition, the code used to turn 37 vuvuzela samples into 1024 simultaneous vuvuzelas, and the code used to generate the visual part of the music videos.

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Exponential Vuvuzelas (Coming Soon) https://david.mandelberg.org/2017/10/10/exponential-vuvuzelas-coming-soon/ https://david.mandelberg.org/2017/10/10/exponential-vuvuzelas-coming-soon/#comments Tue, 10 Oct 2017 17:27:34 +0000 https://david.mandelberg.org/?p=2848 You know what the world really needs more of? Vuvuzela music. Yup. That’s totally a pressing issue in the world today. Well, I’m here to help with a new “musical” composition, Exponential Vuvuzelas. A high quality recording of this work will be released soon on my first ever full‐length album.

Exponential Vuvuzelas Score

Act 1, Crescendo

In the first act, the vuvuzela noisemusic starts gently, and keeps increasing as more and more vuvuzelas join in.

Movement N. 1 Vuvuzela

A lone vuvuzela plays repeatedly for some amount of time.

Movement I. 2 Vuvuzelas

The vuvuzela from the previous movement continues, and one more vuvuzela joins in. This continues for some amount of time.

Movement II. 4 Vuvuzelas

The vuvuzelas from the previous movement continue, and two more vuvuzelas join in. This continues for some amount of time.

Movement III. 8 Vuvuzelas

The vuvuzelas from the previous movement continue, and four more vuvuzelas join in. This continues for some amount of time.

Movement IV. 16 Vuvuzelas

The vuvuzelas from the previous movement continue, and eight more vuvuzelas join in. This continues for some amount of time.

Movement V. 32 Vuvuzelas

The vuvuzelas from the previous movement continue, and 16 more vuvuzelas join in. This continues for some amount of time.

Movement VI. 64 Vuvuzelas

The vuvuzelas from the previous movement continue, and 32 more vuvuzelas join in. This continues for some amount of time.

Movement VII. 128 Vuvuzelas

The vuvuzelas from the previous movement continue, and 64 more vuvuzelas join in. This continues for some amount of time.

Movement VIII. 256 Vuvuzelas

The vuvuzelas from the previous movement continue, and 128 more vuvuzelas join in. This continues for some amount of time.

Movement IX. 512 Vuvuzelas

The vuvuzelas from the previous movement continue, and 256 more vuvuzelas join in. This continues for some amount of time.

Movement X. 1024 Vuvuzelas

The vuvuzelas from the previous movement continue, and 512 more vuvuzelas join in. This continues for some amount of time.

Act 2, Diminuendo

In the second and thankfully, final, act, the vuvuzelas finally go away.

Movement I. 1024–0 Vuvuzelas: “Outro”

The vuvuzelas from the last movement in the previous act continue to play until they run out of breath, without starting up again. The movement ends when the last vuvuzela is done.

Movement N. 0 Vuvuzelas: “A much needed break for your ears”

All vuvuzelas remain silent. This lasts for as long as is needed for listeners to realize that the work is done.

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Managing My Music Collection https://david.mandelberg.org/2017/10/04/managing-my-music-collection/ https://david.mandelberg.org/2017/10/04/managing-my-music-collection/#respond Wed, 04 Oct 2017 22:47:39 +0000 https://david.mandelberg.org/?p=2809 As my music collection has grown, I’ve cobbled together a handful of procedures for managing it from my Ubuntu desktop. This post is primarily for my own benefit so I don’t forget parts of it, but I’m publishing it in case it’s useful to anybody else. For background, the collection is currently at 12,320 tracks, and growing. The vast majority is from (in decreasing order) CDs, vinyl records, and digital downloads. My general strategy is to save as much of any originals as possible in a lossless format (currently, FLAC), and generate smaller, lossy copies of the music as needed. I rely heavily on MusicBrainz for all metadata.

Directory layout

  • archive: Loosely organized files that are not for listening directly, e.g., un‐split digitized vinyl records
  • master.rw: Well organized, master copy of the collection
  • master: Read-only view of master.rw
  • profiles: Various copies of the collection, derived from master

Getting data off of the original media

Ripping CDs

  1. Figure out what sort of disc it is, using cdrdao disk-info. Sometimes there are unlisted data tracks that this discovers.
  2. Use Sound Juicer to get the Disc ID to submit to MusicBrainz.
  3. Use Sound Juicer to extract FLAC files from the audio tracks, into archive/cd/artist-name/album-name. I manually changed its dconf setting for paranoia to ['fragment', 'overlap', 'scratch', 'repair'].
  4. In archive/cd/artist-name/album-name, run cdrdao read-toc d01s01.toc (replacing d01 with the appropriate disc number) to extract the table of contents for the audio session.
  5. If there are any other sessions, extract them by running cdrdao read-cd --session 2 --datafile d01s02.iso d01s02.toc, replacing the disc and session numbers as appropriate, and changing the data file’s extension if appropriate.
  6. If any of the extra sessions contain music or music videos, extract those to individual files.

Digitizing and splitting vinyl records

(This procedure can probably easily be adapted for tapes or other analog sources, but my experience so far is primarily with vinyl records.)

  1. Create a new directory archive/vinyl/album-name, and change into it.
  2. If there’s more than one disc, make a text file in the directory with a note about what order the sides will be digitized in. E.g., for an auto‐sequence album, note that the sides will be digitized in order of side number, not one disc at a time.
  3. If there’s anything else that would affect digitization, note it in a text file. E.g., note if the record is monophonic, or if it will need speed and pitch adjustments.
  4. Plug in the USB turntable, and run record-vinyl project.flac to start recording audio. (Before writing record-vinyl, I had tried Audacity and Ardour for this step. Audacity froze and crashed too often, and Ardour had occasional buffer under‐runs when I did anything else with the computer at the same time. It’s definitely possible that I could have gotten either of them to work better with more effort, but the script wasn’t hard to write.)
  5. For each side, place the side on the turntable, clean it, and play it. If there are any skips, make a text file in the directory with a list of every track that contains a skip.
  6. Stop record-vinyl.
  7. If there were any skips, use Audacity to clean them up, and save the result as a new file. If the pitch and speed need adjustment, do that and save the result as a new file. Do not down‐mix to mono yet, because it’s occasionally easier to split tracks with the fake stereo signal, due to more noise in one channel than the other. (I save the result as a new file instead of going straight to track splitting, to avoid relying on being able to read Audacity project files in the future if I ever want to make any changes.)

    screenshot of Audacity showing a vinyl record with a skipping section selected
    Skipping audio selected, before being removed
  8. Open the un‐split audio file in Audacity, to split it into individual tracks:
    1. Switch to spectrogram view. Drag the bottom of the track down to make it as vertically large as possible, while still leaving space for a small label track at the bottom. (I’ve found this makes it much easier to see the boundaries between tracks.)
    2. For each visible track boundary (which should show up on the spectrogram as background noise with no signal), select from the end of the boundary to the start of that track (which is either the end of the previous label, or the beginning of the disc side). Listen to about a second at a time at each end of the track to make sure the boundaries are at the right place, then create a label in the label track. Within each disc side, there should be no gaps between labels, and no overlapping labels.

      screenshot of Audacity showing a spectrogram of the boundary between two tracks, with one of the tracks selected
      View after creating a label for a track
    3. Compare labels against the printed track list, and adjust as needed. If there are multiple tracks listed in a place where there’s only one label, split that label into multiple new labels, using the printed track times, the audio, and the spectrogram as a guide. Merge any labels that are all within the same listed track into a single new label. If the track list doesn’t include times, look at the placement of gaps on the disc itself as a guide for the correct track lengths.
    4. Export the label track, since it’s a simple text format with all the relevant info for splitting.
    5. If needed, down‐mix the audio to mono.
    6. Export the audio from each label to individual files.

Downloading digital media

  1. Download the files to a subdirectory of archive.
  2. Leave the originals in archive, and make a copy for tagging and moving to master.rw.

Tagging music files and adding them to the collection

  1. Get a front cover image, potentially by scanning the cover art. For large cover art, e.g., of 12″ records, use Hugin to stitch together multiple scans.
  2. Make sure there’s a correct MusicBrainz release, either by adding a new one, or by using an existing one and fixing or completing it if needed. For a CD, attach the extracted Disc ID if needed. I’ve found m17n’s rfc1345 input method very helpful for typing all the punctuation (e.g., curly quotes, various dashes) and scripts (e.g., Cyrillic, Hebrew, Arabic, Greek) in my music collection, without needing to learn a bunch of different keyboard layouts.
  3. Add the more basic of my custom folksonomy tags to MusicBrainz: tag the release with added/YYYY/MM/DD to mark when I added it to my collection, and tag tracks with context/hidden-track/pregap, context/hidden-track/separated-by-silence, or context/hidden-track/unlisted as appropriate.
  4. Tag the music files with MusicBrainz Picard. When tagging files with no preexisting tags (e.g., from vinyl), be especially careful when matching files against tracks to tag.
  5. Use Ex Falso to add ReplayGain tags, and then move the files from archive to master.rw. The rename pattern I use for moving the files is /home/dseomn/Music/master.rw/<albumartistsort>/<album>/d<discnumber|<discnumber>|XX>t<tracknumber|<tracknumber>|XX>. <artist> - <title>.
  6. If any of the newly‐moved files have filenames longer than 251 bytes, shorten them to 251 bytes. (251 allows other copies of the collection to add .mp3 or .ogg at the end of the filename.)
  7. Move any non‐audio files (e.g., cover art, CD tables of contents, etc.) into the same directory as the music files.
  8. Run CoHydra with my configuration to generate copies in profiles from master. (This does things like ensuring consistent cover image filenames for media players that need that, filtering out files that media players don’t understand, creating a directory with only music videos, and recoding to lossy formats for devices with limited storage.)

After adding music

As soon as possible after adding new music, listen to it once through. For vinyl, pay attention to make sure that the audio corresponds to the track title, and the track boundaries make sense. For CDs, listen for errors that might be correctable by washing and re‐ripping the CD. After getting more acquainted with the music over time, come back to it to add more of my folksonomy tags, then add those tags to the files with Picard.

Every once in a while, run lint-analog-audio-rips to find vinyls that I started digitizing and forgot to finish. Also, scan the entire collection with Picard to pick up relevant changes in MusicBrainz data.

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