Challenge: a dataset of English-to-Dutch news translations enriched with translation process data is available for free . three students of a Master's programme in Translation were asked to translate 50 different English journalistic texts of approximately 250 tokens each.
Approach: They propose to make a learner corpus of English-to-Dutch news translations enriched with translation process data.
Outcome: The dataset can be used in translation process research, learner corpus research, and corpus-based translation studies.

Similar Papers

DiHuTra: a Parallel Corpus to Analyse Differences between Human Translations (2022.lrec-1)

Copied to clipboard

Challenge: a new corpus of human translations contains both professional and student translations of news and reviews texts.
Approach: They propose to use the data to compare human and professional translations of news and reviews in a new corpus which contains both professional and student translations.
Outcome: The proposed corpus contains professional and student translations of news and reviews and a subcorpus containing reviews into Finnish.
Small Data, Big Impact: Leveraging Minimal Data for Effective Machine Translation (2023.acl-long)

Copied to clipboard

Challenge: Existing datasets are not economical to create large-scale datasets, but for low-resource languages, a few thousand professionally translated sentence pairs can be useful.
Approach: They propose to use a dataset to train machine translation models on pre-existing and synthetic data to augment them with millions of sentences through backtranslation.
Outcome: The proposed model can cover hundreds of languages with high quality training data even when smaller but lower quality datasets are used.
Multilingual Word Segmentation: Training Many Language-Specific Tokenizers Smoothly Thanks to the Universal Dependencies Corpus (L18-1)

Copied to clipboard

Challenge: Towards language scalability, major progress has been achieved in multilingual language technology in recent years.
Approach: They propose a tokenizer that can be trained from any Universal Dependencies corpus dataset . they argue that tokenization should be seen as a supervised task and scalability requires a software engineering process across languages.
Outcome: The proposed tokenizer can be trained from any dataset in the corpus UD2 . the proposed software tool relies on elephant to perform the training .
GECO-MT: The Ghent Eye-tracking Corpus of Machine Translation (2022.lrec-1)

Copied to clipboard

Challenge: Despite improvements in machine translation output, remarkable differences can be observed when comparing machine translations (MT) and human translations.
Approach: They describe a corpus of eye movement data collected during natural reading of a human translation and a machine translation of . they use this corpus to investigate the effect of machine translation on the reading process and the effects of various error types on reading.
Outcome: The proposed corpus will be used in future research to investigate the effect of machine translation on the reading process and the effects of various error types on reading.
TutorialBank: A Manually-Collected Corpus for Prerequisite Chains, Survey Extraction and Resource Recommendation (P18-1)

Copied to clipboard

Challenge: TutorialBank is a publicly available dataset that aims to facilitate NLP education and research . a google search of "Natural Language Processing" returns over 100 million hits with papers, tutorials, 1 http://aan.how blog posts, codebases and other related online resources.
Approach: They have manually collected and categorized over 5,600 resources on NLP . they have created a search engine and command-line tool to search the corpus .
Outcome: The tutorial bank dataset is the largest manually-picked corpus of resources intended for NLP education . it includes lists of research topics, relevant resources for each topic, prerequisite relations among topics .
LibriS2S: A German-English Speech-to-Speech Translation Corpus (2022.lrec-1)

Copied to clipboard

Challenge: Recent advances in speech-to-text translation have led to significant improvements, but the availability of appropriate training data is limiting.
Approach: They propose a new text-to-speech and speech-tospech translation model that directly learns to generate the speech signal based on the pronunciation of the source language.
Outcome: The proposed model learns to generate speech signal based on pronunciation of source language.
BasqueParl: A Bilingual Corpus of Basque Parliamentary Transcriptions (2022.lrec-1)

Copied to clipboard

Challenge: a new corpus of Basque parliamentary transcripts is released to study political discourse in contrasting languages . a corpus containing political discourses from public institutions can be used for computational social science research .
Approach: They present a corpus from Basque parliamentary transcripts and enrich it with metadata related to relevant attributes of speakers and speeches.
Outcome: The proposed corpus is characterized by heavy Basque-Spanish code-switching . it provides interesting insights about language use of political representatives across time, parties and gender .
Negative language transfer in learner English: A new dataset (2021.naacl-main)

Copied to clipboard

Challenge: This dataset contains annotated error causes for learner writing errors that tie learner mistakes to structures from their first language.
Approach: They propose a learner English dataset enhanced with annotated error causes and concrete examples of learner errors that relate to their first languages.
Outcome: The proposed dataset will be used to analyze learner errors related to language transfer from the learners’ first language.
Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation (L18-1)

Copied to clipboard

Challenge: Recent work in spoken language translation (SLT) has attempted to build end-to-end speech-totext translation without using source language transcription during learning or decoding.
Approach: They propose to augment an existing (monolingual) corpus: LibriSpeech.
Outcome: The proposed corpus is derived from read audiobooks from the LibriVox project and has been carefully segmented and aligned.
Recovering document annotations for sentence-level bitext (2024.findings-acl)

Copied to clipboard

Challenge: In machine translation, historical models were incapable of handling longer contexts, so the lack of document-level datasets was less noticeable.
Approach: They propose a document-level filtering technique that discards document- level metadata.
Outcome: The proposed method improves translation without degradation of sentence-level translation.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations