Papers › TEASEL: A Transformer-Based Speech-Prefixed Language Model
TEASEL: A Transformer-Based Speech-Prefixed Language Model
Mehdi Arjmand, Mohammad Javad Dousti, Hadi Moradi
Multimodal language analysis is a burgeoning field of NLP that aims to simultaneously model a speaker's words, acoustical annotations, and facial expressions. In this area, lexicon features usually outperform other modalities because they are pre-trained on large corpora via Transformer-based models. Despite their strong performance, training a new self-supervised learning (SSL) Transformer on any modality is not usually attainable due to insufficient data, which is the case in multimodal language learning. This work proposes a Transformer-Based Speech-Prefixed Language Model called TEASEL to approach the mentioned constraints without training a complete Transformer model. TEASEL model includes speech modality as a dynamic prefix besides the textual modality compared to a conventional language model. This method exploits a conventional pre-trained language model as a cross-modal Transformer model. We evaluated TEASEL for the multimodal sentiment analysis task defined by CMU-MOSI dataset. Extensive experiments show that our model outperforms unimodal baseline language models by 4% and outperforms the current multimodal state-of-the-art (SoTA) model by 1% in F1-score. Additionally, our proposed method is 72% smaller than the SoTA model.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Multimodal Sentiment Analysis | CMU-MOSI | TEASEL | Acc-2 | 87.5 | #5 of 12 | Archive leaderboard | report |
| Multimodal Sentiment Analysis | CMU-MOSI | TEASEL | Acc-7 | 47.52 | #5 of 12 | Archive leaderboard | report |
| Multimodal Sentiment Analysis | CMU-MOSI | TEASEL | Corr | 0.836 | #5 of 12 | Archive leaderboard | report |
| Multimodal Sentiment Analysis | CMU-MOSI | TEASEL | F1 | 85 | #5 of 12 | Archive leaderboard | report |
| Multimodal Sentiment Analysis | CMU-MOSI | TEASEL | MAE | 0.64 | #5 of 12 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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