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Found 10 papers, 0 papers with code
Crowd-sourcing annotation of complex NLU tasks: A case study of argumentative content annotation
Recent advancements in machine reading and listening comprehension involve the annotation of long texts.
A Dataset of General-Purpose Rebuttal
In Natural Language Understanding, the task of response generation is usually focused on responses to short texts, such as tweets or a turn in a dialog.
Towards Effective Rebuttal: Listening Comprehension using Corpus-Wide Claim Mining
To this end, we collected a large dataset of $400$ speeches in English discussing $200$ controversial topics, mined claims for each topic, and asked annotators to identify the mined claims mentioned in each speech.
Listening Comprehension over Argumentative Content
We applied baseline methods addressing the task, to be used as a benchmark for future work over this dataset.
Automatic Speech Recognition (ASR)
Machine Reading Comprehension
+1
What did you Mention? A Large Scale Mention Detection Benchmark for Spoken and Written Text
We describe a large, high-quality benchmark for the evaluation of Mention Detection tools.
A Recorded Debating Dataset
This paper describes an English audio and textual dataset of debating speeches, a unique resource for the growing research field of computational argumentation and debating technologies.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Joint Learning of Correlated Sequence Labelling Tasks Using Bidirectional Recurrent Neural Networks
The stream of words produced by Automatic Speech Recognition (ASR) systems is typically devoid of punctuations and formatting.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
