{"url":"/dataset/sstorycloze","name":"sStoryCloze","full_name":"Spoken Story Cloze","description_markdown":"The sStoryCloze refers to the Spoken StoryCloze benchmark, which is a spoken version of the StoryCloze dataset. The StoryCloze dataset consists of five-sentence commonsense stories, where the task is to predict the ending of a story given the first four sentences and two possible endings, one of which is the correct ending and the other is a distractor. The sStoryCloze evaluates the model's capabilities to capture fine-grained causal and temporal commonsense relations in spoken language. It assesses the model's ability to generate coherent and contextually appropriate continuations given a spoken prompt. The dataset is used to evaluate the performance of SpeechLMs in understanding and generating spoken narratives.","description_withheld":null,"homepage":"https://github.com/slp-rl/SpokenStoryCloze","introduced_date":"2023-05-22","introduced_date_note":null,"introduced_by":{"paper":"/paper/textually-pretrained-speech-language-models","title":"Textually Pretrained Speech Language Models","first_author":"Michael Hassid","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["sStoryCloze"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}