Kolomogorov Complexity is a “universal theory of information”. “how much information is contained in a string”

The Kolomogorov Complexity of a string \(x\) is the length of the shortest description, \(|d(x)|\)

information as description

Key idea: the more we can compress a string, the more information it contains. The amount of information in a string \(x\) is the length of the shortest description of \(x\).

aside

For some \((M,w)\), we are about to write short strings of it; how do we encode it?

Where:

\begin{equation} ||X-Y||_{\infty} = \max \{| x_{i} - y_{i} |, x \in X, y \in Y} \} \end{equation}

DOI: 10.3389/fcomp.2021.624694

One-Liner

Proposed a large multimodal approach to embed auditory info + biomarkers for baseline classification.

Novelty

Developed a massively multimodal audio-to-embedding correlation system that maps audio to biomarker information collected (mood, memory, respiratory) and demonstrated its ability to discriminate cough results for COVID. (they were looking for AD; whoopsies)

Notable Methods

• Developed a feature extraction model for AD detection named Open Voice Brain Model
• Collected a dataset on people coughing and correlated it with biomarkers

Key Figs

Figure 2

This is MULTI-MODAL as heck

see Lambda Calculus