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1
Zukunft der Sprache – Zukunft der Nation? : Verhandlungen des Jiddischen und Jüdischen im Kontext der Czernowitzer Sprachkonferenz
Reichert, Carmen (Herausgeber); Bannasch, Bettina (Herausgeber); Wildfeuer, Alfred (Herausgeber). - Berlin : De Gruyter Oldenbourg, 2022
UB Frankfurt Linguistik
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2
Teaching and testing second language pragmatics and interaction : a practical guide
Röver, Carsten. - London : Routledge, 2022
BLLDB
UB Frankfurt Linguistik
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3
Teaching and learning pragmatics : where language and culture meet
Ishihara, Noriko; Cohen, Andrew D.. - London : Routledge, 2022
BLLDB
UB Frankfurt Linguistik
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4
Mehrsprachigkeit im Kontext des Kurmancî-Kurdischen und des Deutschen : eine Fallstudie aus einer kurdisch-deutschen Kindertagesstätte
Kırgız, Yaşar. - Tübingen : Narr Francke Attempto, 2022
BLLDB
UB Frankfurt Linguistik
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5
A guide to school services in speech-language pathology
Seidel, Courtney L.; Schraeder, Trici. - San Diego : Plural Publishing, 2022
BLLDB
UB Frankfurt Linguistik
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6
The ambiguity of English as a lingua franca : politics of language and race in South Africa
Rudwick, Stephanie. - London : Routledge, 2022
BLLDB
UB Frankfurt Linguistik
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7
Explanations in sociosyntactic variation
Christensen, Tanya Karoli; Jensen, Torben Juel. - Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2022
Leibniz-Zentrum Allgemeine Sprachwissenschaft
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8
Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP
In: https://hal.inria.fr/hal-03540069 ; 2022 (2022)
BASE
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9
A fine-grained recognition of Named Entities in ELTeC collection using cascades
In: Final Action Event of COST Action Distant Reading for European Literary History ; https://hal.archives-ouvertes.fr/hal-03615219 ; Final Action Event of COST Action Distant Reading for European Literary History, Christof Schöch, Apr 2022, Krakow, Poland ; https://www.distant-reading.net/events/conference-programme/ (2022)
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10
The genetic architecture of language functional connectivity
In: ISSN: 1053-8119 ; EISSN: 1095-9572 ; NeuroImage ; https://hal.sorbonne-universite.fr/hal-03566120 ; NeuroImage, Elsevier, 2022, 249, pp.118795. ⟨10.1016/j.neuroimage.2021.118795⟩ (2022)
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11
RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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12
Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources
In: https://hal.inria.fr/hal-03550289 ; 2022 (2022)
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13
Source or target first? Comparison of two post-editing strategies with translation students
In: https://hal.archives-ouvertes.fr/hal-03546151 ; 2022 (2022)
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14
Meta-Analysis of the Functional Neuroimaging Literature with Probabilistic Logic Programming
In: https://hal.archives-ouvertes.fr/hal-03590714 ; 2022 (2022)
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15
Automatic Normalisation of Early Modern French
In: https://hal.inria.fr/hal-03540226 ; 2022 (2022)
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16
Offline Corpus Augmentation for English-Amharic Machine Translation
In: 2022 The 5th International Conference on Information and Computer Technologies ; https://hal.archives-ouvertes.fr/hal-03547539 ; 2022 The 5th International Conference on Information and Computer Technologies, Mar 2022, New York, United States (2022)
Abstract: International audience ; The purpose of this study was to investigate the effect of corpus augmentation on the quality of English-Amharic Machine Translation (MT). In fact, trigram and four-gram Statistical Machine Translation (SMT) language models, as well as Neural Machine Translation (NMT) models based on Gated Recurrent Units (GRU) were used. They were trained independently using both the original and augmented corpus to see how the augmentation of the corpus affects the translation quality of these models. These two corpora (original and augmented) contain 225,304 and 463,796 English-Amharic parallel sentences respectively. To complete the corpus augmentation challenge, an offline token level tokenization technique was used. This technique (corpus augmentation) was used before any other MT processes were started. Among several token-level tokenization mechanisms, random insertion, replacement, deletion, and swapping approaches were chosen and implemented. After both models had been trained, the Bilingual Evaluation Understudy (BLEU) ratings were collected and analyzed. Our results demonstrate that the models trained with the augmented corpus outperform their corresponding models (models trained with the original corpus) in terms of BLEU scores. As a result, we can conclude that corpus augmentation did indeed help in the improvement of the performance of both SMT and NMT translation systems.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Amharic language; Corpus Augmentation; GRU; Machine Translation; NMT; SMT; Token level augmentation
URL: https://hal.archives-ouvertes.fr/hal-03547539
https://hal.archives-ouvertes.fr/hal-03547539/file/ICICT2022Augmented_corpusFinal%20Draft.pdf
https://hal.archives-ouvertes.fr/hal-03547539/document
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17
The (white) ears of Ofsted: a raciolinguistic perspective on the listening practices of the schools inspectorate
Cushing, I; Snell, J. - : Cambridge University Press, 2022
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18
Non-sexist Language in Vacancy Titles: A Proposal for Drafting and Translation in International Organisations
In: Journal of International Women's Studies (2022)
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19
The effects of various combinations of form-focused instruction techniques on the acquisition of English articles by second language learners of English
Lloyd, Jackie S.. - : Brock University, 2022
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20
A Scoping Review of Teaching Practices for Linguistically Diverse Students in Ontario
Kittani, Lana. - 2022
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