DOI: 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