yet another flowchart abstraction
Last edited: August 8, 2025yafa!
Syntax
[ (Circle) -> [square] -> (Circle) | (Circle) ]
[ (circle) ]
[ <lt1>(self loop) -> <lt1> ]
EXPRESSION = EXPRESSION' ARROW NODE | EXPRESSION' ALTERNATION NODE | STRING
EXPRESSION' = EXPRESSION' ARROW NODE | EXPRESSION' ALTERNATION NODE | NODE
NODE = SQUARE | CIRCLE | ANCHOR
SQUARE = "[" EXPRESSION "] | ANCHOR "[" EXPRESSION "]
ANCHOR = "<" LABEL ">"
ALTERNATION = "|"
ARROW = SARROW | DARROW
SARROW = "->"
DARROW = "=>"
LABEL = r"[\w\d]+"
STRING = LABEL | "\"" ".*" "\""
Semantics
Young's Modulus
Last edited: August 8, 2025Young’s Modulus is a mechanical property that measures the stiffness of a solid material.
It measures the ratio between mechanical stress \(\sigma\) and the relative resulting strain \(\epsilon\).
And so, very simply:
\begin{equation} E = \frac{\sigma }{\epsilon } \end{equation}
Thinking about this, silly puddy deforms very easily given a little stress, so it would have low Young’s Modulus (\(\sigma \ll \epsilon\)); and visa versa. https://aapt.scitation.org/doi/10.1119/1.17116?cookieSet=1
Yuan 2021
Last edited: August 8, 2025DOI: 10.3389/fcomp.2020.624488
One-Liner
Used an ERNIE trained on transcripts for classification; inclusion of pause encoding made results better.
Novelty
- Instead of just looking at actual speech content, look at pauses specific as a feature engineering task
- \(89.6\%\) on the ADReSS Challenge dataset
Notable Methods

Applied FA with pause encoding with standard .cha
semantics (short pauses, medium pauses, long pauses). Shoved all of this into an ERNIE.
Assay for performance was LOO
z-test
Last edited: August 8, 2025A z-test is a hypothesis test for statistical significance between two sample proportions. Before it can be conducted, it must meet the conditions for inference for a z-test.
conditions for inference (z-test)
- has to be random
- has to be reasonably normal (vis a vi test for normality)
- each sample has to be independent (or 10% rule)
use a z-statistic to find p-value
- Given a sample proportion, calculate the sample proportion standard deviation (given on the formula sheet)
- Then, divide the difference between measured and null proportions to figure \(z\)
that is,