Data Selection

method ID: dataselection

Related Papers

Data Selection With Fewer Words

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

We present a method that improves data selection by combining a hybrid word/part-of-speech representation for corpora, with the idea of distinguishing between rare and frequent events. We validate our approach …...

28137

Neural Machine Translation Training in a Multi-Domain Scenario

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractIn this paper, we explore alternative ways to train a neural machine translation system in a multi-domain scenario. We investigate data concatenation (with fine tuning), model stacking (multi-level fine tuning), …...

20768

Data selection for NMT using Infrequent n-gram Recovery

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

AbstractNeural Machine Translation (NMT) has achieved promising results comparable with Phrase-Based Statistical Machine Translation (PBSMT). However, to train a neural translation engine, much more powerful machines are required than those …...

2869

Data Selection for Unsupervised Translation of German–Upper Sorbian

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractThis paper describes the methods behind the systems submitted by the University of Groningen for the WMT 2020 Unsupervised Machine Translation task for German–Upper Sorbian. We investigate the usefulness of …...

27498

DiDi’s Machine Translation System for WMT2020

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractThis paper describes the DiDi AI Labs’ submission to the WMT2020 news translation shared task. We participate in the translation direction of Chinese->English. In this direction, we use the Transformer …...

27674

Data Filtering using Cross-Lingual Word Embeddings

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractData filtering for machine translation (MT) describes the task of selecting a subset of a given, possibly noisy corpus with the aim to maximize the performance of an MT system …...

21857

Small Model and In-Domain Data Are All You Need

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractI participated in the WMT shared news translation task and focus on one high resource language pair: English and Chinese (two directions, Chinese to English and English to Chinese). The …...

27769

Tencent Translation System for the WMT21 News Translation Task

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractThis paper describes Tencent Translation systems for the WMT21 shared task. We participate in the news translation task on three language pairs: Chinese-English, English-Chinese and German-English. Our systems are built …...

27775

TenTrans Large-Scale Multilingual Machine Translation System for WMT21

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractThis paper describes TenTrans large-scale multilingual machine translation system for WMT 2021. We participate in the Small Track 2 in five South East Asian languages, thirty directions: Javanese, Indonesian, Malay, …...

27742

HW-TSC Translation Systems for the WMT22 Chat Translation Task

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractThis paper describes the submissions of Huawei Translation Services Center (HW-TSC) to WMT22 chat translation shared task on English-Germany (en-de) bidirection with results of zore-shot and few-shot tracks. We use …...

27455

Learning to Selectively Learn for Weakly Supervised Paraphrase Generation with Model-based Reinforcement Learning

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractParaphrase generation is an important language generation task attempting to interpret user intents and systematically generate new phrases of identical meanings to the given ones. However, the effectiveness of paraphrase …...

21356

No Domain Left behind

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractWe participated in the WMT General MT task and focus on four high resource language pairs: English to Chinese, Chinese to English, English to Japanese and Japanese to English). The …...

27554