Papers Word Alignment
“Word Alignment” 태그가 달린 논문 564편 · 필터 해제
Unsupervised Cross-Lingual Part-of-Speech Tagging for Truly Low-Resource Scenarios
We describe a fully unsupervised cross-lingual transfer approach for part-of-speech (POS) tagging under a truly low resource scenario. We assume access to parallel translations between the target language and one or more…
Cross-Lingual TransferPart-Of-Speech TaggingPOSPOS Tagging+2Alibaba Submission to the WMT20 Parallel Corpus Filtering Task
This paper describes the Alibaba Machine Translation Group submissions to the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment. In the filtering task, three main methods are applied to evaluate the quality…
DiversityLanguage IdentificationMachine TranslationSentence+3Volctrans Parallel Corpus Filtering System for WMT 2020
In this paper, we describe our submissions to the WMT20 shared task on parallel corpus filtering and alignment for low-resource conditions. The task requires the participants to align potential parallel sentence pairs ou…
RerankingSentenceWord AlignmentLearning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora
We propose a new approach for learning contextualised cross-lingual word embeddings based on a small parallel corpus (e.g. a few hundred sentence pairs). Our method obtains word embeddings via an LSTM encoder-decoder mod…
Bilingual Lexicon InductionCross-Lingual Word EmbeddingsDecoderSentence+3FastEmit: Low-latency Streaming ASR with Sequence-level Emission Regularization
Streaming automatic speech recognition (ASR) aims to emit each hypothesized word as quickly and accurately as possible. However, emitting fast without degrading quality, as measured by word error rate (WER), is highly ch…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech Recognition+1Counterfactual Variable Control for Robust and Interpretable Question Answering
Deep neural network based question answering (QA) models are neither robust nor explainable in many cases. For example, a multiple-choice QA model, tested without any input of question, is surprisingly "capable" to predi…
Causal InferencecounterfactualMultiple-choiceMultiple Choice Question Answering (MCQA)+2A Generalized Constraint Approach to Bilingual Dictionary Induction for Low-Resource Language Families
The lack or absence of parallel and comparable corpora makes bilingual lexicon extraction a difficult task for low-resource languages. The pivot language and cognate recognition approaches have been proven useful for ind…
Bilingual Lexicon InductionTranslationWord AlignmentConstructing Uyghur Name Entity Recognition System using Neural Machine Translation Tag Projection
Although named entity recognition achieved great success by introducing the neural networks, it is challenging to apply these models to low resource languages including Uyghur while it depends on a large amount of annota…
Machine Translationnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+4Generative latent neural models for automatic word alignment
Word alignments identify translational correspondences between words in a parallel sentence pair and are used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems or to perform…
Machine TranslationSentenceText GenerationTranslation+1Neural Baselines for Word Alignment
Word alignments identify translational correspondences between words in a parallel sentence pair and is used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems , or to perfor…
Machine TranslationSentenceTranslationWord AlignmentOpusFilter: A Configurable Parallel Corpus Filtering Toolbox
This paper introduces OpusFilter, a flexible and modular toolbox for filtering parallel corpora. It implements a number of components based on heuristic filters, language identification libraries, character-based languag…
Domain AdaptationLanguage IdentificationTranslationWord AlignmentLearning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy
Word translation is an integral part of language translation. In machine translation, each language is considered a domain with its own word embedding. The alignment between word embeddings allows linking semantically eq…
Machine TranslationSentenceTranslationWord Alignment+2Neural Simultaneous Speech Translation Using Alignment-Based Chunking
In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency and quality. We propose a neural machin…
ChunkingMachine TranslationNMTTranslation+1Evaluating Explanation Methods for Neural Machine Translation
Recently many efforts have been devoted to interpreting the black-box NMT models, but little progress has been made on metrics to evaluate explanation methods. Word Alignment Error Rate can be used as such a metric that …
Machine TranslationNMTTranslationWord AlignmentLine-a-line: A Tool for Annotating Word-Alignments
We here describe line-a-line, a web-based tool for manual annotation of word-alignments in sentence-aligned parallel corpora. The graphical user interface, which builds on a design template from the Jigsaw system for inv…
Multilingual Word EmbeddingsSentenceWord AlignmentWord EmbeddingsFrameNet Annotations Alignment using Attention-based Machine Translation
This paper presents an approach to project FrameNet annotations into other languages using attention-based neural machine translation (NMT) models. The idea is to use an NMT encoder-decoder attention matrix to propose a …
DecoderMachine TranslationNMTTranslation+1Automatic Construction of Aramaic-Hebrew Translation Lexicon
Aramaic is an ancient Semitic language with a 3,000 year history. However, since the number of Aramaic speakers in the world hasdeclined, Aramaic is in danger of extinction. In this paper, we suggest a methodology for au…
SentenceTranslationWord AlignmentBuilding an English-Chinese Parallel Corpus Annotated with Sub-sentential Translation Techniques
Human translators often resort to different non-literal translation techniques besides the literal translation, such as idiom equivalence, generalization, particularization, semantic modulation, etc., especially when the…
Machine TranslationSentenceTranslationWord AlignmentWord Rotator's Distance
A key principle in assessing textual similarity is measuring the degree of semantic overlap between two texts by considering the word alignment. Such alignment-based approaches are intuitive and interpretable; however, t…
Semantic SimilaritySemantic Textual SimilaritySentenceWord Alignment+1Accurate Word Alignment Induction from Neural Machine Translation
Despite its original goal to jointly learn to align and translate, prior researches suggest that Transformer captures poor word alignments through its attention mechanism. In this paper, we show that attention weights DO…
DecoderMachine TranslationMulti-Task LearningTranslation+1