According to research development, what is required to differentiate paralinguistic features from linguistic features in speech analysis?

Separate, specialized models trained on vast datasets of emotionally labeled speech

The advanced analysis of speech requires specialized modeling because linguistic features (the actual words spoken) and paralinguistic features (tone, stress, emotion conveyed through acoustics) must be assessed distinctly. To accurately capture emotion—such as discerning if a customer was agitated while speaking—separate, specialized models are necessary. These models must be trained extensively on vast datasets where the speech has already been labeled for its emotional content. This computational feat allows the system to correlate acoustic signals with emotional states, a capability far beyond the scope of initial ASR systems.