DE eng

Search in the Catalogues and Directories

Page: 1 2
Hits 1 – 20 of 22

1
XTREME-S: Evaluating Cross-lingual Speech Representations ...
BASE
Show details
2
Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation ...
BASE
Show details
3
Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning ...
BASE
Show details
4
mSLAM: Massively multilingual joint pre-training for speech and text ...
Bapna, Ankur; Cherry, Colin; Zhang, Yu. - : arXiv, 2022
BASE
Show details
5
Examining Scaling and Transfer of Language Model Architectures for Machine Translation ...
BASE
Show details
6
MAESTRO: Matched Speech Text Representations through Modality Matching ...
BASE
Show details
7
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
In: https://hal.inria.fr/hal-03177623 ; 2021 (2021)
BASE
Show details
8
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets ...
BASE
Show details
9
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents ...
BASE
Show details
10
Joint Unsupervised and Supervised Training for Multilingual ASR ...
Bai, Junwen; Li, Bo; Zhang, Yu. - : arXiv, 2021
BASE
Show details
11
Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation ...
BASE
Show details
12
Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference ...
BASE
Show details
13
Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference ...
BASE
Show details
14
Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
In: Zhang, Biao; Bapna, Ankur; Sennrich, Rico; Firat, Orhan (2021). Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation. In: International Conference on Learning Representations, Virtual, 3 May 2021 - 7 May 2021, ICLR. (2021)
BASE
Show details
15
Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation ...
BASE
Show details
16
Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus ...
Abstract: Large text corpora are increasingly important for a wide variety of Natural Language Processing (NLP) tasks, and automatic language identification (LangID) is a core technology needed to collect such datasets in a multilingual context. LangID is largely treated as solved in the literature, with models reported that achieve over 90% average F1 on as many as 1,366 languages. We train LangID models on up to 1,629 languages with comparable quality on held-out test sets, but find that human-judged LangID accuracy for web-crawl text corpora created using these models is only around 5% for many lower-resource languages, suggesting a need for more robust evaluation. Further analysis revealed a variety of error modes, arising from domain mismatch, class imbalance, language similarity, and insufficiently expressive models. We propose two classes of techniques to mitigate these errors: wordlist-based tunable-precision filters (for which we release curated lists in about 500 languages) and transformer-based ... : Accepted to COLING 2020. 9 pages with 8 page abstract ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://arxiv.org/abs/2010.14571
https://dx.doi.org/10.48550/arxiv.2010.14571
BASE
Hide details
17
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation ...
BASE
Show details
18
Investigating Multilingual NMT Representations at Scale ...
BASE
Show details
19
Simple, Scalable Adaptation for Neural Machine Translation ...
BASE
Show details
20
Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges ...
BASE
Show details

Page: 1 2

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
22
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern