DE eng

Search in the Catalogues and Directories

Page: 1 2 3 4 5 6
Hits 1 – 20 of 116

1
Multilingual CoNaLa Datset, train data ...
Zhiruo Wang; Cuenca, Grace; Shuyan Zhou. - : Zenodo, 2022
BASE
Show details
2
Multilingual CoNaLa Datset, train data ...
Zhiruo Wang; Cuenca, Grace; Shuyan Zhou. - : Zenodo, 2022
BASE
Show details
3
AUTOLEX: An Automatic Framework for Linguistic Exploration ...
BASE
Show details
4
MCoNaLa: A Benchmark for Code Generation from Multiple Natural Languages ...
BASE
Show details
5
A Systematic Evaluation of Large Language Models of Code ...
BASE
Show details
6
Expanding Pretrained Models to Thousands More Languages via Lexicon-based Adaptation ...
BASE
Show details
7
Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation
In: Transactions of the Association for Computational Linguistics, 7, 313–325 ; ISSN: 2307-387X (2022)
BASE
Show details
8
Lightly Supervised Quality Estimation
Waibel, Alex; Niehues, Jan; Stüker, Sebastian. - : Association for Computational Linguistics, 2022
BASE
Show details
9
MasakhaNER: Named entity recognition for African languages
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)
BASE
Show details
10
Phoneme Recognition through Fine Tuning of Phonetic Representations: a Case Study on Luhya Language Varieties ...
Abstract: Models pre-trained on multiple languages have shown significant promise for improving speech recognition, particularly for low-resource languages. In this work, we focus on phoneme recognition using Allosaurus, a method for multilingual recognition based on phonetic annotation, which incorporates phonological knowledge through a language-dependent allophone layer that associates a universal narrow phone-set with the phonemes that appear in each language. To evaluate in a challenging real-world scenario, we curate phone recognition datasets for Bukusu and Saamia, two varieties of the Luhya language cluster of western Kenya and eastern Uganda. To our knowledge, these datasets are the first of their kind. We carry out similar experiments on the dataset of an endangered Tangkhulic language, East Tusom, a Tibeto-Burman language variety spoken mostly in India. We explore both zero-shot and few-shot recognition by fine-tuning using datasets of varying sizes (10 to 1000 utterances). We find that fine-tuning of ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2104.01624
https://arxiv.org/abs/2104.01624
BASE
Hide details
11
Few-shot Language Coordination by Modeling Theory of Mind ...
BASE
Show details
12
Systematic Inequalities in Language Technology Performance across the World's Languages ...
BASE
Show details
13
Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models ...
BASE
Show details
14
Multi-view Subword Regularization ...
BASE
Show details
15
MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learning ...
BASE
Show details
16
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation ...
BASE
Show details
17
When Does Translation Require Context? A Data-driven, Multilingual Exploration ...
BASE
Show details
18
Breaking Down Multilingual Machine Translation ...
BASE
Show details
19
Efficient Test Time Adapter Ensembling for Low-resource Language Varieties ...
BASE
Show details
20
Distributionally Robust Multilingual Machine Translation ...
Zhou, Chunting; Levy, Daniel; Li, Xian. - : arXiv, 2021
BASE
Show details

Page: 1 2 3 4 5 6

Catalogues
0
0
2
0
1
0
0
Bibliographies
1
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
113
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern