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  # LibriS2S
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  This repo contains scripts and alignment data to create a dataset build further upon [librivoxDeEn](https://www.cl.uni-heidelberg.de/statnlpgroup/librivoxdeen/) such that it contains (German audio, German transcription, English audio, English transcription) quadruplets and can be used for Speech-to-Speech translation research. Because of this, the alignments are released under the same [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-nc-sa/4.0/) <div>
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  These alignments were collected by downloading the English audiobooks and using [aeneas](https://github.com/readbeyond/aeneas) to align the book chapters to the transcripts. For more information read the original [paper](https://arxiv.org/abs/2204.10593) (Presented at LREC 2022)
 
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+ ---
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+ annotations_creators: []
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+ language:
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+ - en
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+ - de
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+ language_creators: []
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+ license:
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+ - cc-by-nc-sa-4.0
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+ multilinguality:
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+ - multilingual
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+ pretty_name: LibriS2S German-English Speech and Text pairs
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets: []
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+ tags:
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+ - LibriS2S
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+ - LibrivoxDeEn
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+ - Speech-to-Speech translation
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+ - LREC2022
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+ task_categories:
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+ - text-to-speech
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+ - automatic-speech-recognition
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+ - translation
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+ task_ids: []
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+ ---
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+
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  # LibriS2S
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  This repo contains scripts and alignment data to create a dataset build further upon [librivoxDeEn](https://www.cl.uni-heidelberg.de/statnlpgroup/librivoxdeen/) such that it contains (German audio, German transcription, English audio, English transcription) quadruplets and can be used for Speech-to-Speech translation research. Because of this, the alignments are released under the same [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-nc-sa/4.0/) <div>
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  These alignments were collected by downloading the English audiobooks and using [aeneas](https://github.com/readbeyond/aeneas) to align the book chapters to the transcripts. For more information read the original [paper](https://arxiv.org/abs/2204.10593) (Presented at LREC 2022)