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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Evaluating the Morphosyntactic Well-formedness of Generated Texts ... Pratapa, Adithya; Anastasopoulos, Antonios; Rijhwani, Shruti. - : arXiv, 2021 BASE Show details 2 Evaluating the Morphosyntactic Well-formedness of Generated Texts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Anastasopoulos, Antonios; Chaudhary, Aditi. - : Underline Science Inc., 2021 BASE Show details 3 Lexically Aware Semi-Supervised Learning for OCR Post-Correction ... Rijhwani, Shruti; Rosenblum, Daisy; Anastasopoulos, Antonios. - : arXiv, 2021 BASE Show details 4 Lexically-Aware Semi-Supervised Learning for OCR Post-Correction ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Anastasopoulos, Antonios; Neubig, Graham. - : Underline Science Inc., 2021 BASE Show details 5 AlloVera: a multilingual allophone database Mortensen, David,; Li, Xinjian; Littell, Patrick; Michaud, Alexis; Rijhwani, Shruti; Anastasopoulos, Antonios; Black, Alan; Metze, Florian; Neubig, Graham In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020) Abstract: International audience ; We introduce a new resource, AlloVera, which provides mappings from 218 allophones to phonemes for 14 languages. Phonemes are contrastive phonological units, and allophones are their various concrete realizations, which are predictable from phonological context. While phonemic representations are language specific, phonetic representations (stated in terms of (allo)phones) are much closer to a universal (language-independent) transcription. AlloVera allows the training of speech recognition models that output phonetic transcriptions in the International Phonetic Alphabet (IPA), regardless of the input language. We show that a "universal" allophone model, Allosaurus, built with AlloVera, outperforms "universal" phonemic models and language-specific models on a speech-transcription task. We explore the implications of this technology (and related technologies) for the documentation of endangered and minority languages. We further explore other applications for which AlloVera will be suitable as it grows, including phonological typology. Keyword: [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing; Allophones; Phoneme URL: https://halshs.archives-ouvertes.fr/halshs-02527046/file/MultilingualAllophoneResourceforNearUniversalASR.pdf https://halshs.archives-ouvertes.fr/halshs-02527046/document https://halshs.archives-ouvertes.fr/halshs-02527046 BASE Hide details 6 AlloVera: A Multilingual Allophone Database ... Mortensen, David R.; Li, Xinjian; Littell, Patrick. - : arXiv, 2020 BASE Show details 7 A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization ... Neubig, Graham; Rijhwani, Shruti; Palmer, Alexis. - : arXiv, 2020 BASE Show details 8 AlloVera: a multilingual allophone database Mortensen, David,; Li, Xinjian; Littell, Patrick... In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020) BASE Show details

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