EV / New EnergyOEM sound-quality teams + Tier 2 trim / HVAC / door locks
EV Cabin "Small Sounds" Sound-Quality Evaluation
01
Pain Points
- !Without engine masking, an EV amplifies and exposes door-closing, air-vent, and rattle sounds.
- !Transient events must be detected accurately before evaluation; manual segmentation is unreliable.
- !Subjective "cheapness" complaints lack objective quantification and a basis for regression.
02
The Tinia Approach
Auto-locate transient events + four-metric psychoacoustic characterization; with subjective ratings, use AutoML to predict the "premium/cheap" tendency.
Capture transient eventsLoudness + Sharpness + Roughness + TonalityFeature mergeAutoML discrimination (optional)
03
Nodes Used
Active Segment Detectionactive_segment
Auto-locate transient sound eventsLoudnessloudness
Event loudnessSharpnesssharpness
Event sharpnessRoughnessroughness
Event roughnessTonalitytonality
Event tonalityFeature Mergefeature_merge
Merge features across eventsCore nodes; add or remove steps as needed for your data and standards — the node graph is always editable.
04
Expected Output
- Psychoacoustic metrics for each sound event.
- A subjective-objective regression discriminant function (AutoML distillation, optional).
- An objective basis for quantifying "small sound" issues.
Reference Standards / Engineering PracticeOEM internal standards · ECMA-418-2
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