{"url":"/dataset/spoken-squad","name":"Spoken-SQuAD","full_name":null,"description_markdown":"In SpokenSQuAD, the document is in spoken form, the input question is in the form of text and the answer to each question is always a span in the document. The following procedures were used to generate spoken documents from the original SQuAD dataset. First, the Google text-to-speech system was used to generate the spoken version of the articles in SQuAD. Then CMU Sphinx was sued to generate the corresponding ASR transcriptions. The SQuAD training set was used to generate the training set of Spoken SQuAD, and SQuAD development set was used to generate the testing set for Spoken SQuAD. If the answer of a question did not exist in the ASR transcriptions of the associated article, the question-answer pair was removed from the dataset because these examples are too difficult for listening comprehension machine at this stage.\n\nSource: [https://github.com/chiahsuan156/Spoken-SQuAD](https://github.com/chiahsuan156/Spoken-SQuAD)\nImage Source: [https://github.com/chiahsuan156/Spoken-SQuAD](https://github.com/chiahsuan156/Spoken-SQuAD)","description_withheld":null,"homepage":"https://github.com/chiahsuan156/Spoken-SQuAD","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/spoken-squad-a-study-of-mitigating-the-impact","title":"Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening Comprehension","first_author":"Chia-Hsuan Li","url":null},"license":null,"modalities":[{"name":"Speech","url":"/datasets/modality/speech"}],"tasks":[{"name":"Speech Recognition","url":"/task/speech-recognition","datasets_with_task":"/datasets/task/speech-recognition"},{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"},{"name":"Reading Comprehension","url":"/task/reading-comprehension","datasets_with_task":"/datasets/task/reading-comprehension"},{"name":"Spoken Language Understanding","url":"/task/spoken-language-understanding","datasets_with_task":"/datasets/task/spoken-language-understanding"}],"languages":[],"variants":["Spoken-SQuAD"],"data_loaders":[{"repo":"https://github.com/chiahsuan156/Spoken-SQuAD","url":"https://github.com/chiahsuan156/Spoken-SQuAD","frameworks":[]}],"num_papers_in_archive":24,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/spoken-language-understanding-on-spoken-squad","task":"Spoken Language Understanding","dataset_variant":"Spoken-SQuAD","rows":4,"metrics":["F1 score"],"first_row_in_archive_order":{"model":"ALBERT","paper":"/paper/end-to-end-spoken-conversational-question","metrics":{"F1 score":"77.1"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/end-to-end-spoken-conversational-question","title":"End-to-end Spoken Conversational Question Answering: Task, Dataset and Model","date":"2022-04-29","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/speechbert-cross-modal-pre-trained-language","title":"SpeechBERT: An Audio-and-text Jointly Learned Language Model for End-to-end Spoken Question Answering","date":"2019-10-25","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/mitigating-the-impact-of-speech-recognition-1","title":"Mitigating the Impact of Speech Recognition Errors on Spoken Question Answering by Adversarial Domain Adaptation","date":"2019-04-16","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/spoken-squad-a-study-of-mitigating-the-impact","title":"Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening Comprehension","date":"2018-04-01","rows_on_this_dataset":1,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+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."}