| Challenge: | a new corpus of speeches from campaign events is used to predict moments of audience applause . lexical features carry the most information, but a variety of features are predictive . |
| Approach: | They propose a corpus of speeches from campaign events in the months leading up to the 2016 election and develop new models for applause. |
| Outcome: | The proposed model predicts moments of audience applause from speeches at campaign rallies, rallies and rallies. |
Similar Papers
Creating a Corpus of Gestures and Predicting the Audience Response based on Gestures in Speeches of Donald Trump (2020.lrec-1)
Copied to clipboard
| Challenge: | a study aims to explore the role of speech pauses and gestures alone as predictors of audience reaction without other types of speech information. |
| Approach: | They analyze two speeches by Barack Obama and use them to predict audience reaction . they find that long pauses and co-speech gestures alone predict audience response . |
| Outcome: | The proposed models can predict audience reaction without other types of speech information. |
Come hither or go away? Recognising pre-electoral coalition signals in the news (2021.emnlp-main)
Copied to clipboard
Ines Rehbein, Simone Paolo Ponzetto, Anna Adendorf, Oke Bahnsen, Lukas Stoetzer, Heiner Stuckenschmidt
| Challenge: | In this paper, we decompose the task of recognizing from the news coverage leading up to an election the (un)willingness of political parties to form a coalition into two related, but distinct tasks. |
| Approach: | They propose a task of recognizing from news coverage the (un)willingness of political parties to form a coalition from text and a sub-task of predicting the polarity of the signal. |
| Outcome: | The proposed approach improves over a strong monolingual transfer learning baseline. |
Out of the Mouths of MPs: Speaker Attribution in Parliamentary Debates (2024.lrec-main)
Copied to clipboard
| Challenge: | Identifying who says what to whom is an essential prerequisite for analysing human communication. |
| Approach: | They propose a new corpus for speaker attribution in german parliamentary debates . the data includes more than 7,700 manually annotated events of speech, thought and writing . they then apply their model to predict speech events in 20 years of debates and investigate the use of factives in the rhetoric of MPs. |
| Outcome: | The proposed model predicts speech events in 20 years of debates and investigates the use of factives in the rhetoric of MPs. |
Summarizing Speech: A Comprehensive Survey (2025.emnlp-main)
Copied to clipboard
Fabian Retkowski, Maike Züfle, Andreas Sudmann, Dinah Pfau, Shinji Watanabe, Jan Niehues, Alexander Waibel
| Challenge: | Podcasts and other audiovisual content are becoming more and more a part of everyday communication and the digital age is changing from text to voice. |
| Approach: | They synthesize the current state of the field and highlight the need for realistic evaluation benchmarks and multilingual datasets. |
| Outcome: | The proposed frameworks are based on evaluation protocols and datasets and highlight the need for realistic benchmarks and multilingual datasets. |
Machine-Aided Annotation for Fine-Grained Proposition Types in Argumentation (2020.lrec-1)
Copied to clipboard
| Challenge: | a corpus of 2016 debates and commentary contains 4,648 argumentative propositions annotated with fine-grained proposition types. |
| Approach: | They propose a machine learning-human workflow for annotating for four complex proposition types . they demonstrate with preliminary analysis of rhetorical strategies and structure in presidential debates . |
| Outcome: | The proposed method can be used by technical researchers seeking more nuanced representations of argument . it can also be used to analyze rhetorical strategies and structure in presidential debates . |
Yes, we can! Mining Arguments in 50 Years of US Presidential Campaign Debates (P19-1)
Copied to clipboard
| Challenge: | Political debates are a natural application scenario for Argument Mining. |
| Approach: | They propose an argument mining approach to political debates that uses argument components to annotate 39 political debate from the last 50 years of US presidential campaigns. |
| Outcome: | The proposed approach outperforms baselines in argument mining over political debates. |
Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump’s Presidential Campaigns (2026.eacl-long)
Copied to clipboard
| Challenge: | Large Language Models excel in a wide range of instruction-following tasks, but their grasp of social science concepts remains underexplored. |
| Approach: | They evaluate pre-trained large language models to identify populist discourse . they use a RoBERTa classifier to analyze campaign speeches by Donald Trump . |
| Outcome: | The proposed model outperforms all new-era instruction-tuned LLMs on populist discourse analysis. |
SpanPredict: Extraction of Predictive Document Spans with Neural Attention (2021.naacl-main)
Copied to clipboard
| Challenge: | identifying predictive text in clinical notes can be as important as the predictions themselves . identifying specific content in clinical note descriptions may illuminate previously unknown risk factors . |
| Approach: | They propose a method for identifying predictive text in clinical notes . they use linear attention to formalize the problem as predictive extraction . |
| Outcome: | The proposed model preserves differentiability and allows scalable inference via stochastic gradient descent. |
Let’s do it “again”: A First Computational Approach to Detecting Adverbial Presupposition Triggers (P18-1)
Copied to clipboard
| Challenge: | a novel task of predicting adverbial presupposition triggers is useful for natural language generation . a focus is on a new attention mechanism for predicting presuposition trigger . |
| Approach: | They propose a new attention mechanism for predicting adverbial presupposition triggers . they propose to augment a baseline neural network without additional trainable parameters . |
| Outcome: | The proposed model outperforms baseline models in predicting adverbial presupposition triggers. |
Open-Vocabulary Argument Role Prediction For Event Extraction (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Existing studies on event extraction depend on pre-defined argument roles . despite great progress, many studies still rely on hand-crafted ontologies . |
| Approach: | They propose an unsupervised framework for customizing argument roles for event extraction . they propose a human-annotated event extraction dataset with 143 customized argument roles . |
| Outcome: | The proposed framework outperforms existing methods on an event extraction dataset. |