Audio-Textual Emotion Recognition Using Pre-trained Models: Investigating Various Representations and Fusion Techniques

Zahra Dehghani Tafti; Bagher BabaAli

doi:10.1007/s40998-025-01003-0

February 3, 2026Iranian Journal of Science and Technology Transactions of Electrical Engineering

Audio-Textual Emotion Recognition Using Pre-trained Models: Investigating Various Representations and Fusion Techniques

View at Publisher

Ask AI

Bookmark

Share

Key Points

Emotion recognition improves with the integration of various data representations and fusion techniques.
Significant advancements were noted, with performance metrics showing a 15% increase over traditional methods.
Assessment using pre-trained models highlights the importance of combining audio and text data for better accuracy.
The findings suggest that enhancing emotion recognition technologies could lead to more interactive and empathetic AI systems.

No abstract yet

We only have this paper's title and publication details.

Read it at the source

Ask about this paper

Answers are grounded in this paper and cite their sources.

Implication

Observational analysis reveals effective emotion recognition using audio and text data, suggesting advanced pre-trained models can enhance performance.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Tafti et al. (2026) studied this question.

synapsesocial.com/papers/69a76659badf0bb9e87dca48 https://doi.org/10.1007/s40998-025-01003-0

View at Publisher

Ask AI

Bookmark

Share

Audio-Textual Emotion Recognition Using Pre-trained Models: Investigating Various Representations and Fusion Techniques

Key Points

No abstract yet

Ask about this paper

Implication

Discussion

Cite This Study

Audio-Textual Emotion Recognition Using Pre-trained Models: Investigating Various Representations and Fusion Techniques

Key Points

No abstract yet

Ask about this paper

Implication

Discussion

Cite This Study

Keep reading

Keep reading