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Found 17 papers, 11 papers with code
DIALECTBENCH: A NLP Benchmark for Dialects, Varieties, and Closely-Related Languages
This allows for a comprehensive evaluation of NLP system performance on different language varieties.
MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling
A major consideration in multilingual language modeling is how to best represent languages with diverse vocabularies and scripts.
Extracting Lexical Features from Dialects via Interpretable Dialect Classifiers
Identifying linguistic differences between dialects of a language often requires expert knowledge and meticulous human analysis.
That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?
In experiments, we compare MT-specific models and language models for (i) their preference when given an ambiguous subsentence, (ii) their sensitivity to disambiguating context, and (iii) the performance disparity between figurative and literal source sentences.
Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models
Language models have graduated from being research prototypes to commercialized products offered as web APIs, and recent works have highlighted the multilingual capabilities of these products.
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users.
Intriguing Properties of Compression on Multilingual Models
Multilingual models are often particularly dependent on scaling to generalize to a growing number of languages.
MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
African languages are spoken by over a billion people, but are underrepresented in NLP research and development.
What a Creole Wants, What a Creole Needs
We demonstrate, through conversations with Creole experts and surveys of Creole-speaking communities, how the things needed from language technology can change dramatically from one language to another, even when the languages are considered to be very similar to each other, as with Creoles.
AfriWOZ: Corpus for Exploiting Cross-Lingual Transferability for Generation of Dialogues in Low-Resource, African Languages
The language with the most transferable properties is the Nigerian Pidgin English, with a human-likeness score of 78. 1%, of which 34. 4% are unanimous.
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation
However, evaluation of the trade-offs incurred by popular compression techniques has been centered on high-resource datasets.
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
With the success of large-scale pre-training and multilingual modeling in Natural Language Processing (NLP), recent years have seen a proliferation of large, web-mined text datasets covering hundreds of languages.
MasakhaNER: Named Entity Recognition for African Languages
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders.
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages
Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved.
Towards Supervised and Unsupervised Neural Machine Translation Baselines for Nigerian Pidgin
Nigerian Pidgin is arguably the most widely spoken language in Nigeria.
PidginUNMT: Unsupervised Neural Machine Translation from West African Pidgin to English
In this work, we perform the first NLP work on the most popular variant of the language, providing three major contributions.
