FROID Psique · Glossary

The technology, in plain language.

Ten concepts for understanding FROID Psique. The analogies make reading easier; they do not replace definitions or evidence of validity.

The ten concepts

01 · AI

Neural network

A layered model that learns patterns from examples. Like successive filters, the layers transform the input into useful representations. Performance depends on the task, the data and the evaluation — there is no automatic superiority.

02 · Retrieval

RAG

Retrieval-augmented generation. The search brings relevant content to support the model's answer: like consulting a library before writing. The answer can still be wrong.

03 · Voice

IPM

Multimodal Power Index. Despite its historical name, in the current composition it organizes the magnitude of acoustic deviations. It is a reading of variation, not a mental health score.

04 · Voice

IDM

Multimodal Deviation Index. It preserves the average direction of vocal deviations, distinguishing increases and decreases in energy. It does not measure conflict between speech and face.

05 · Acoustics

12 acoustic bands

Bands that organize vocal energy. Think of the channels of an equalizer, not twelve emotions. There is no validated association between each band and a feeling.

06 · Face

Seven facial families

Groupings of compatible movement configurations. They work like categories in a catalog; they do not determine the person's emotional state.

07 · Movement

FACS and AUs

FACS describes movements in Action Units. The product uses approximate estimates: 16 fields, 15 with mappings conditioned on the measurements received, and AU23 with no ascertainment. It is not certified coding.

08 · Voice

MFCC

Mel-frequency cepstral coefficients: a mathematical representation of spectral characteristics of speech. In the product, MFCC7 and MFCC9 are tracked measures, not isolated diagnoses.

09 · Exploration

Sub-harmonics

The product uses this name for exploratory indicators associated with vocal analysis. The described 5–12 Hz range must not be presented as a validated clinical biomarker or as a diagnosis.

10 · Privacy

k-anonymity

A property of a set in which each record shares combinations of selected attributes with at least k−1 others. It does not mean zero risk of re-identification; its application depends on the data and on the conditions of the analysis. In Data-Froid, an aggregate query is only answered for groups with k ≥ 7 records; below that it is refused. The floor limits the query; it does not make re-identification impossible.

See the concepts in the context of use