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MasakhaNER: Named entity recognition for African languages
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In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03350962 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021, ⟨10.1162/tacl⟩ (2021)
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Speech technology for unwritten languages
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In: ISSN: 2329-9290 ; EISSN: 2329-9304 ; IEEE/ACM Transactions on Audio, Speech and Language Processing ; https://hal.inria.fr/hal-02480675 ; IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2020, ⟨10.1109/TASLP.2020.2973896⟩ (2020)
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AlloVera: a multilingual allophone database
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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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AlloVera: a multilingual allophone database
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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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Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop
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In: ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01709578 ; ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Alberta, Canada (2018)
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Evaluating phonemic transcription of low-resource tonal languages for language documentation
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In: LREC 2018 (Language Resources and Evaluation Conference) ; https://halshs.archives-ouvertes.fr/halshs-01709648 ; LREC 2018 (Language Resources and Evaluation Conference), May 2018, Miyazaki, Japan. pp.3356-3365 (2018)
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Integrating automatic transcription into the language documentation workflow: Experiments with Na data and the Persephone toolkit
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In: ISSN: 1934-5275 ; EISSN: 1934-5275 ; Language Documentation & Conservation ; https://halshs.archives-ouvertes.fr/halshs-01841979 ; Language Documentation & Conservation, University of Hawaiʻi Press 2018, 12, pp.393-429 ; hdl.handle.net/10125/24793 (2018)
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Integrating automatic transcription into the language documentation workflow: Experiments with Na data and the Persephone toolkit
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In: ISSN: 1934-5275 ; EISSN: 1934-5275 ; Language Documentation & Conservation ; https://halshs.archives-ouvertes.fr/halshs-01841979 ; Language Documentation & Conservation, University of Hawaiʻi Press 2018, 12, pp.393-429 ; hdl.handle.net/10125/24793 (2018)
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| 9 |
Evaluating phonemic transcription of low-resource tonal languages for language documentation
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In: LREC 2018 (Language Resources and Evaluation Conference) ; https://halshs.archives-ouvertes.fr/halshs-01709648 ; LREC 2018 (Language Resources and Evaluation Conference), May 2018, Miyazaki, Japan. pp.3356-3365 (2018)
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Phonemic transcription of low-resource tonal languages
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In: ISSN: 1834-7037 ; Australasian Language Technology Association Workshop 2017 ; https://halshs.archives-ouvertes.fr/halshs-01656683 ; Australasian Language Technology Association Workshop 2017, Dec 2017, Brisbane, Australia. pp.53-60 (2017)
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Abstract:
International audience ; Transcription of speech is an important part of language documentation, and yet speech recognition technology has not been widely harnessed to aid linguists. We explore the use of a neural network architecture with the connectionist temporal classification loss function for phonemic and tonal transcription in a language documentation setting. In this framework, we explore jointly modelling phonemes and tones versus modelling them separately, and assess the importance of pitch information versus phonemic context for tonal prediction. Experiments on two tonal languages, Yongning Na and Eastern Chatino, show the changes in recognition performance as training data is scaled from 10 minutes to 150 minutes. We discuss the findings from incorporating this technology into the linguistic workflow for documenting Yongning Na, which show the method's promise in improving efficiency, minimizing typographical errors, and maintaining the transcription's faithfulness to the acoustic signal, while highlighting phonetic and phonemic facts for linguistic consideration.
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Keyword:
[SHS.LANGUE]Humanities and Social Sciences/Linguistics; Automatic language processing; Automatic speech recognition; Automatic speech transcription; Documentation linguistique; Endangered languages; Interdisciplinarity; Language documentation; Multimedia corpora; Online databases; Open access; Open-source software; Oral literature; Sound archives; Traitement automatique de la parole; Transcription automatique; Transcription phonémique
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URL: https://halshs.archives-ouvertes.fr/halshs-01656683/file/Adams_et_al2017_PhonemicTranscription.pdf
https://halshs.archives-ouvertes.fr/halshs-01656683
https://halshs.archives-ouvertes.fr/halshs-01656683/document
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Phonemic transcription of low-resource tonal languages
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In: ISSN: 1834-7037 ; Australasian Language Technology Association Workshop 2017 ; https://halshs.archives-ouvertes.fr/halshs-01656683 ; Australasian Language Technology Association Workshop 2017, Dec 2017, Brisbane, Australia. pp.53-60 (2017)
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