Search Results for author:
Found 32 papers, 6 papers with code
Translation Memories as Baselines for Low-Resource Machine Translation
Low-resource machine translation research often requires building baselines to benchmark estimates of progress in translation quality.
NRC Systems for the 2020 Inuktitut-English News Translation Task
We describe the National Research Council of Canada (NRC) submissions for the 2020 Inuktitut-English shared task on news translation at the Fifth Conference on Machine Translation (WMT20).
ReadAlong Studio: Practical Zero-Shot Text-Speech Alignment for Indigenous Language Audiobooks
While the alignment of audio recordings and text (often termed “forced alignment”) is often treated as a solved problem, in practice the process of adapting an alignment system to a new, under-resourced language comes with significant challenges, requiring experience and expertise that many outside of the speech community lack.
NRC-CNRC Machine Translation Systems for the 2021 AmericasNLP Shared Task
We describe the NRC-CNRC systems submitted to the AmericasNLP shared task on machine translation.
NRC Systems for Low Resource German-Upper Sorbian Machine Translation 2020: Transfer Learning with Lexical Modifications
We describe the National Research Council of Canada (NRC) neural machine translation systems for the German-Upper Sorbian supervised track of the 2020 shared task on Unsupervised MT and Very Low Resource Supervised MT.
Requirements and Motivations of Low-Resource Speech Synthesis for Language Revitalization
This paper describes the motivation and development of speech synthesis systems for the purposes of language revitalization.
The Indigenous Languages Technology project at NRC Canada: An empowerment-oriented approach to developing language software
This paper surveys the first, three-year phase of a project at the National Research Council of Canada that is developing software to assist Indigenous communities in Canada in preserving their languages and extending their use.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Neural Polysynthetic Language Modelling
In the literature, languages like Finnish or Turkish are held up as extreme examples of complexity that challenge common modelling assumptions.
The Nunavut Hansard Inuktitut--English Parallel Corpus 3.0 with Preliminary Machine Translation Results
This paper describes a newly released sentence-aligned Inuktitut{--}English corpus based on the proceedings of the Legislative Assembly of Nunavut, covering sessions from April 1999 to June 2017.
A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization
Despite recent advances in natural language processing and other language technology, the application of such technology to language documentation and conservation has been limited.
AlloVera: A Multilingual Allophone Database
While phonemic representations are language specific, phonetic representations (stated in terms of (allo)phones) are much closer to a universal (language-independent) transcription.
Universal Phone Recognition with a Multilingual Allophone System
Multilingual models can improve language processing, particularly for low resource situations, by sharing parameters across languages.
Multi-Source Transformer for Kazakh-Russian-English Neural Machine Translation
We describe the neural machine translation (NMT) system developed at the National Research Council of Canada (NRC) for the Kazakh-English news translation task of the Fourth Conference on Machine Translation (WMT19).
Choosing Transfer Languages for Cross-Lingual Learning
Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages.
Towards a General-Purpose Linguistic Annotation Backend
In this extended abstract, we describe the beginnings of a new project that will attempt to ease this language documentation process through the use of natural language processing (NLP) technology.
Measuring sentence parallelism using Mahalanobis distances: The NRC unsupervised submissions to the WMT18 Parallel Corpus Filtering shared task
The WMT18 shared task on parallel corpus filtering (Koehn et al., 2018b) challenged teams to score sentence pairs from a large high-recall, low-precision web-scraped parallel corpus (Koehn et al., 2018a).
Accurate semantic textual similarity for cleaning noisy parallel corpora using semantic machine translation evaluation metric: The NRC supervised submissions to the Parallel Corpus Filtering task
We present our semantic textual similarity approach in filtering a noisy web crawled parallel corpus using YiSi{---}a novel semantic machine translation evaluation metric.
Finite-state morphology for Kwak'wala: A phonological approach
This paper presents the phonological layer of a Kwak{'}wala finite-state morphological transducer, using the phonological hypotheses of Lincoln and Rath (1986) and the lenient composition operation of Karttunen (1998) to mediate the complicated relationship between underlying and surface forms.
Indigenous language technologies in Canada: Assessment, challenges, and successes
In this article, we discuss which text, speech, and image technologies have been developed, and would be feasible to develop, for the approximately 60 Indigenous languages spoken in Canada.
Optical Character Recognition
Optical Character Recognition (OCR)
+7
Learning Language Representations for Typology Prediction
One central mystery of neural NLP is what neural models "know" about their subject matter.
URIEL and lang2vec: Representing languages as typological, geographical, and phylogenetic vectors
We introduce the URIEL knowledge base for massively multilingual NLP and the lang2vec utility, which provides information-rich vector identifications of languages drawn from typological, geographical, and phylogenetic databases and normalized to have straightforward and consistent formats, naming, and semantics.
PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors
This paper contributes to a growing body of evidence that{---}when coupled with appropriate machine-learning techniques{--}linguistically motivated, information-rich representations can outperform one-hot encodings of linguistic data.
The Role of Context in Neural Morphological Disambiguation
While morphological analyzers can reduce this sparsity by providing morpheme-level analyses for words, they will often introduce ambiguity by returning multiple analyses for the same surface form.
Named Entity Recognition for Linguistic Rapid Response in Low-Resource Languages: Sorani Kurdish and Tajik
This paper describes our construction of named-entity recognition (NER) systems in two Western Iranian languages, Sorani Kurdish and Tajik, as a part of a pilot study of {``}Linguistic Rapid Response{''} to potential emergency humanitarian relief situations.
Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning
We introduce polyglot language models, recurrent neural network models trained to predict symbol sequences in many different languages using shared representations of symbols and conditioning on typological information about the language to be predicted.
Bridge-Language Capitalization Inference in Western Iranian: Sorani, Kurmanji, Zazaki, and Tajik
In Sorani Kurdish, one of the most useful orthographic features in named-entity recognition {--} capitalization {--} is absent, as the language{'}s Perso-Arabic script does not make a distinction between uppercase and lowercase letters.
Morphological parsing of Swahili using crowdsourced lexical resources
We describe a morphological analyzer for the Swahili language, written in an extension of XFST/LEXC intended for the easy declaration of morphophonological patterns and importation of lexical resources.
