Using advanced vocal analysis, Seerium can approximate a speaker’s age, gender, and even their regional origin based on speech patterns, slang, tone, and pacing.
By analyzing vocal frequency, pitch range, and speech pace, the system can estimate whether a speaker is a child, young adult, or elderly.
Machine learning models trained on voice samples distinguish between male, female, and ambiguous gender profiles based on timbre and tone.
Unique slang, pronunciation patterns, and local speech habits allow us to infer a speaker’s regional background or dialect zone.