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AlloVera: a multilingual allophone database
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
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2
AlloVera: A Multilingual Allophone Database ...
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3
Towards Minimal Supervision BERT-based Grammar Error Correction ...
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4
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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5
It's not a Non-Issue: Negation as a Source of Error in Machine Translation ...
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6
Automatic Extraction of Rules Governing Morphological Agreement ...
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7
A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization ...
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8
It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information ...
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9
Universal Phone Recognition with a Multilingual Allophone System ...
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10
It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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11
X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models ...
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12
AlloVera: a multilingual allophone database
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)
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