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Neubig, Graham (115)
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Hits 101 – 116 of 116
101
Integrating automatic transcription into the language documentation workflow: Experiments with Na data and the Persephone toolkit
Michaud, Alexis
;
Adams, Oliver
;
Cohn, Trevor
...
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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102
Evaluating phonemic transcription of low-resource tonal languages for language documentation
Adams, Oliver
;
Cohn, Trevor
;
Neubig, Graham
...
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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103
Integrating Automatic Transcription into the Language Documentation Workflow: Experiments with Na Data and the Persephone Toolkit
Michaud, Alexis
;
Adams, Oliver
;
Cohn, Trevor Anthony
. - : University of Hawaii Press, 2018
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104
Integrating Automatic Transcription into the Language Documentation Workflow: Experiments with Na Data and the Persephone Toolkit
Michaud, Alexis
;
Adams, Oliver
;
Cohn, Trevor Anthony
. - : University of Hawaii Press, 2018
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105
Phonemic transcription of low-resource tonal languages
Adams, Oliver
;
Cohn, Trevor
;
Neubig, Graham
;
Michaud, Alexis
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)
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.
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
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Open-source software
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Oral literature
;
Sound archives
;
Traitement automatique de la parole
;
Transcription automatique
;
Transcription phonémique
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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106
Learning Language Representations for Typology Prediction ...
Malaviya, Chaitanya
;
Neubig, Graham
;
Littell, Patrick
. - : arXiv, 2017
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107
CharManteau: Character Embedding Models For Portmanteau Creation ...
Gangal, Varun
;
Jhamtani, Harsh
;
Neubig, Graham
. - : arXiv, 2017
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108
Phonemic transcription of low-resource tonal languages
Adams, Oliver
;
Cohn, Trevor
;
Neubig, Graham
...
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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109
Neural Lattice-to-Sequence Models for Uncertain Inputs
Sperber, Matthias
;
Neubig, Graham
;
Waibel, Alex
. - : Association for Computational Linguistics, 2017
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110
Lexicons and Minimum Risk Training for Neural Machine Translation: NAIST-CMU at WAT2016 ...
Neubig, Graham
. - : arXiv, 2016
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111
Incorporating Discrete Translation Lexicons into Neural Machine Translation ...
Arthur, Philip
;
Neubig, Graham
;
Nakamura, Satoshi
. - : arXiv, 2016
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112
What Do Recurrent Neural Network Grammars Learn About Syntax? ...
Kuncoro, Adhiguna
;
Ballesteros, Miguel
;
Kong, Lingpeng
. - : arXiv, 2016
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113
Morphological Inflection Generation Using Character Sequence to Sequence Learning ...
Faruqui, Manaal
;
Tsvetkov, Yulia
;
Neubig, Graham
. - : arXiv, 2015
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114
Neural Reranking Improves Subjective Quality of Machine Translation: NAIST at WAT2015 ...
Neubig, Graham
;
Morishita, Makoto
;
Nakamura, Satoshi
. - : arXiv, 2015
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115
Substring-based machine translation
Neubig, Graham
;
Watanabe, Taro
;
Mori, Shinsuke
...
In:
Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media
27 (2013) 2, 139-166
OLC Linguistik
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116
A monotonic statistical machine translation approach to speaking style transformation
Kawahara, Tatsuya
;
Neubig, Graham
;
Akita, Yuya
...
In:
Computer speech and language. - Amsterdam [u.a.] : Elsevier
26 (2012) 5, 349-370
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