Aug 11, 2016 · Abstract: This paper introduces a novel framework for combining the strengths of machine-based and human-based emotion classification.

This paper proposes granularity-adapted classification that can be used as a front-end to drive a recommender, based on emotions from speech. In this context, ...

Granularity-adapted classification that can be used as a front-end to drive a recommender, based on emotions from speech, is proposed, and is an aggregate ...

We conduct extensive experiments to assess the ef- fectiveness of EAT on emotional talking-head generation. Compared to baseline competitors, EAT achieves ...

This paper proposes granularity-adapted classification that can be used as a front-end to drive a recommender, based on emotions from speech. In this context, ...

Audio-based age and gender identification to enhance the recommendation of TV content ... Audio-based granularity-adapted emotion classification. SE Shepstone, ZH ...

Jul 31, 2024 · This approach bridges the gap between audio and text modalities in LLM-based ERC systems, potentially capturing emotion cues that are present in ...

This low-level simulation of human behaviour is usually considered a classification task based on training data but not proof that AI has emotions. Therefore, ...

This research work addresses the problem of music emotion recognition using audio signals. Music emotion recognition research has been gaining ground over ...

This tutorial examines how to detect underlying emotions in recorded speech samples by analyzing the acoustic features of the speech using a classification ...