We were having a conversation recently at work about server naming conventions and it reminded of an article where the author was using a mnemonic word list to name servers. After a little digging, I was able to track it down.

Index

A proper server naming scheme

The original post was A proper server naming scheme over at mnx.io. It is worth a read, but some of the links are outdated. It looks like the original mnemonic encoding project (from Oren Tirosh) that was referenced has vanished. That was the project that contained the word list that I was looking for.

Oren Tirosh’s Mnemonic Encoding Project

I was able to track down a copy of the mnemonicode project. It looks like Oren compiled a list of 1626 words that could be used to encode or decode information. The words have been chosen to be easy to understand when spoken over the phone.

From the readme

Mnemonic tries to be selective about its word list. Its criteria are thus:

Mandatory Criteria:

  • The wordlist contains 1626 words.
  • All words are between 4 and 7 letters long.
  • No word in the list is a prefix of another word (e.g. visit, visitor).
  • Five letter prefixes of words are sufficient to be unique.

Less Strict Criteria:

  • The words should be usable by people all over the world. The list is far from perfect in that respect. It is heavily biased towards western culture and English in particular. The international vocabulary is simply not big enough. One can argue that even words like “hotel” or “radio” are not truly international. You will find many English words in the list but I have tried to limit them to words that are part of a beginner’s vocabulary or words that have close relatives in other european languages. In some cases a word has a different meaning in another language or is pronounced very differently but for the purpose of the encoding it is still ok - I assume that when the encoding is used for spoken communication both sides speak the same language.

  • The words should have more than one syllable. This makes them easier to recognize when spoken, especially over a phone line. Again, you will find many exceptions. For one syllable words I have tried to use words with 3 or more consonants or words with diphthongs, making for a longer and more distinct pronunciation. As a result of this requirement the average word length has increased. I do not consider this to be a problem since my goal in limiting the word length was not to reduce the average length of encoded data but to limit the maximum length to fit in fixed-size fields or a terminal line width.

  • No two words on the list should sound too much alike. Soundalikes such as “sweet” and “suite” are ruled out. One of the two is chosen and the other should be accepted by the decoder’s soundalike matching code or using explicit aliases for some words.

  • No offensive words. The rule was to avoid words that I would not like to be printed on my business card. I have extended this to words that by themselves are not offensive but are too likely to create combinations that someone may find embarrassing or offensive. This includes words dealing with religion such as “church” or “jewish” and some words with negative meanings like “problem” or “fiasco”. I am sure that a creative mind (or a random number generator) can find plenty of embarrassing or offensive word combinations using only words in the list but I have tried to avoid the more obvious ones. One of my tools for this was simply a generator of random word combinations - the problematic ones stick out like a sore thumb.

  • Avoid words with tricky spelling or pronunciation. Even if the receiver of the message can probably spell the word close enough for the soundalike matcher to recognize it correctly I prefer avoiding such words. I believe this will help users feel more comfortable using the system, increase the level of confidence and decrease the overall error rate. Most words in the list can be spelled more or less correctly from hearing, even without knowing the word.

  • The word should feel right for the job. I know, this one is very subjective but some words would meet all the criteria and still not feel right for the purpose of mnemonic encoding. The word should feel like one of the words in the radio phonetic alphabets (alpha, bravo, charlie, delta etc).

The word list

Here is a sample from the middle of the list:

lobster  local    logic    logo     lola     london   
lucas    lunar    machine  macro    madam    madonna  
madrid   maestro  magic    magnet   magnum   mailbox  
major    mama     mambo    manager  manila   marco    
marina   market   mars     martin   marvin   mary     
master   matrix   maximum  media    medical  mega     
melody   memo     mental   mentor   mercury  message  
metal    meteor   method   mexico   miami    micro    
milk     million  minimum  minus    minute   miracle  
mirage   miranda  mister   mixer    mobile   modem    
modern   modular  moment   monaco   monica   monitor  
mono     monster  montana  morgan   motel    motif    
motor    mozart   multi    museum   mustang  natural  
neon     nepal    neptune  nerve    neutral  nevada   
news     next     ninja    nirvana  normal   nova     
novel    nuclear  numeric  nylon    oasis    observe  
ocean    octopus  olivia   olympic  omega    opera    
optic    optimal  orange   orbit    organic  orient   
origin   orlando  oscar    oxford   oxygen   ozone    
pablo    pacific  pagoda   palace   pamela   panama   
pancake  panda    panel    panic    paradox  pardon   
paris    parker   parking  parody   partner  passage

I have reproduced the entire word list here and on GitHubGist to make it easy to find. It was extracted from the mn_wordlist.c file in the project.

Craig G’s MnemonicEncodingWordList Project

After I published this post, Craig created a small project in PowerShell to work with this list. In that project he has the full list in a json document.

Save this for future reference

I don’t have an immediate need for this list, but it took be a bit longer to find it than I expected. I know I could use any word list but this one was carefully crafted and I wanted to preserve it. I hope you find a valuable use for it. I know I am saving this one for later.