Fast transcription of speech in low-resource languages

September 16, 2019 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Mark Hasegawa-Johnson, Camille Goudeseune, Gina-Anne Levow arXiv ID 1909.07285 Category cs.CL: Computation & Language Citations 3 Venue arXiv.org Last Checked 5 months ago
Abstract
We present software that, in only a few hours, transcribes forty hours of recorded speech in a surprise language, using only a few tens of megabytes of noisy text in that language, and a zero-resource grapheme to phoneme (G2P) table. A pretrained acoustic model maps acoustic features to phonemes; a reversed G2P maps these to graphemes; then a language model maps these to a most-likely grapheme sequence, i.e., a transcription. This software has worked successfully with corpora in Arabic, Assam, Kinyarwanda, Russian, Sinhalese, Swahili, Tagalog, and Tamil.
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