Smriti is an approach to help you transform your 12 or 24 word seed phrases into memorizable ones.
There are 2048 words within the BIP-39 wordlist.
This gives an entropy of
While it is difficult for someone to memorize a list of 12 / 24 random words in order,
it is relatively easy for someone to memorize a number of different classes of things.
e.g.
Remember a Movie : Les Miserables
Remember a Fruit : Kiwi
Remember a Bird : Humming bird
Remember a song : The Amen Corner
and so on
The list of such classes (Movie, Fruit, Bird etc.) are ordered which reduces a
burden of the end user.
They only need to remember the names of objects from each class
but has no need to maintain the order in their head.
So the math works out to
for the 12 and 24 word seed phrase respectively
where we have m different classes of things to memorize, with
If we assume each class to have the same number of objects,
this table lists how many different classes we will need
In reality not all the classes will have the same number of objects but the table gives us a rough idea of how easy it will be to create a memorizable set of classes.
For example, it is very easy to create 30 classes with 446 elements each.
However memorizing 30 different objects is very hard for the end user.
On the other hand memorizing only 10 elements is easy for the end user,
but constructing 10 classes with 80 million + elements is not easy.
e.g. We were able to compile a list of international movies of only 45000+ elements.
Right now I am constructing the list of classes and elements within each that will make your seed phrases memorizable. Here are some suggestions
- Movies
- Birds
- Historical Figures
- Song / Music
Contributions are welcome as pull requests or discussions in Github issues.
Feel free to reach out to me at my website