{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/augmenting-librispeech-with-french","title":"Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation","arxiv_id":"1802.03142","date":"2018-02-09","proceeding":"LREC 2018 5","authors":["Ali Can Kocabiyikoglu","Laurent Besacier","Olivier Kraif"],"abstract":"Recent works in spoken language translation (SLT) have attempted to build\nend-to-end speech-to-text translation without using source language\ntranscription during learning or decoding. However, while large quantities of\nparallel texts (such as Europarl, OpenSubtitles) are available for training\nmachine translation systems, there are no large (100h) and open source parallel\ncorpora that include speech in a source language aligned to text in a target\nlanguage. This paper tries to fill this gap by augmenting an existing\n(monolingual) corpus: LibriSpeech. This corpus, used for automatic speech\nrecognition, is derived from read audiobooks from the LibriVox project, and has\nbeen carefully segmented and aligned. After gathering French e-books\ncorresponding to the English audio-books from LibriSpeech, we align speech\nsegments at the sentence level with their respective translations and obtain\n236h of usable parallel data. This paper presents the details of the processing\nas well as a manual evaluation conducted on a small subset of the corpus. This\nevaluation shows that the automatic alignments scores are reasonably correlated\nwith the human judgments of the bilingual alignment quality. We believe that\nthis corpus (which is made available online) is useful for replicable\nexperiments in direct speech translation or more general spoken language\ntranslation experiments.","url_abs":"http://arxiv.org/abs/1802.03142v1","url_pdf":"http://arxiv.org/pdf/1802.03142v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"augmenting-librispeech-with-french","repo_url":"https://github.com/alicank/Translation-Augmented-LibriSpeech-Corpus","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"automatic-speech-recognition-2","task_name":"Automatic Speech Recognition"},{"task_slug":"automatic-speech-recognition","task_name":"Automatic Speech Recognition (ASR)"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"speech-to-text","task_name":"Speech-to-Text"},{"task_slug":"speech-to-text-translation","task_name":"Speech-to-Text Translation"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1802.03142","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}