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INTRODUCTION |
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Multilingual LibriSpeech (MLS) dataset is a large multilingual corpus |
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suitable for speech research. The dataset is derived from read audiobooks |
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from LibriVox and consists of 8 languages - English, German, Dutch, French, |
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Spanish, Italian, Portuguese and Polish. |
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STATISTICS |
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Language | train(hrs) | dev(hrs) | test(hrs) |
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English | 44659.74 | 15.75 | 15.55 |
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German | 1966.51 | 14.28 | 14.29 |
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Dutch | 1554.24 | 12.76 | 12.76 |
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French | 1076.58 | 10.07 | 10.07 |
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Spanish | 917.68 | 9.99 | 10.00 |
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Italian | 247.38 | 5.18 | 5.27 |
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Portuguese | 160.96 | 3.64 | 3.74 |
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Polish | 103.65 | 2.08 | 2.14 |
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DIRECTORY STRUCTURE |
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A typical top-level directory layout |
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. |
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βββ metainfo.txt # Info about the LibriVox data used in the dataset (one row per chapter) |
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βββ dev # Dev (validation) subset |
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βΒ Β βββ segments.txt |
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βΒ Β βββ transcripts.txt |
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βΒ Β βββ audio |
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β βββ ... |
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βββ test # Test subset |
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βΒ Β βββ segments.txt |
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βΒ Β βββ transcripts.txt |
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βΒ Β βββ audio |
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β βββ ... |
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βββ train # Train subset |
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βΒ Β βββ segments.txt # LibriVox audio links and segment start/end timestamps (in sec) for each audio file |
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βΒ Β βββ transcripts.txt # Transcripts file with audio file name as key |
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βΒ Β βββ audio |
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β β βββ 10148 # LibriVox speaker ID |
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β β β βββ 10119 # LibriVox book ID |
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β β β β βββ 10148_10119_000000.flac # 16Khz audio file |
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β β β β βββ 10148_10119_000001.flac |
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β β β β βββ ... |
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β β β βββ ... |
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β β βββ ... |
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βΒ Β βββ limited_supervision # Limited supervision training sets (10 min, 1 hr and 10 hr) |
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β βββ 1hr # Data of the 1h split (made up of 6 folds of 10 min) |
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β β βββ 0 # first 10 min fold |
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β β β βββ handles.txt # List of audio handles for the split |
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β β βββ ... |
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β β βββ 6 # last 10 min fold |
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β β βββ handles.txt |
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β βββ 9hr # Remaining data of the 10h split (10h=1h+9h) |
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β βββ handles.txt |
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βββ LICENSE # License info |
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βββ README |
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For more information, see the paper "MLS: A Large-Scale Multilingual Dataset for Speech Research", Vineel Pratap, Qiantong Xu, Anuroop Sriram, Gabriel Synnaeve and Ronan Collobert, INTERSPEECH 2020. |
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