Papers Word Alignment
“Word Alignment” 태그가 달린 논문 564편 · 필터 해제
Learning Trilingual Dictionaries for Urdu -- Roman Urdu -- English
In this paper, we present an effort to generate a joint Urdu, Roman Urdu and English trilingual lexicon using automated methods. We make a case for using statistical machine translation approaches and parallel corpora fo…
Machine TranslationTranslationWord AlignmentEn-Ar Bilingual Word Embeddings without Word Alignment: Factors Effects
This paper introduces the first attempt to investigate morphological segmentation on En-Ar bilingual word embeddings using bilingual word embeddings model without word alignment (BilBOWA). We investigate the effect of se…
SegmentationSentenceWord AlignmentWord EmbeddingsBilingual Lexicon Induction through Unsupervised Machine Translation
A recent research line has obtained strong results on bilingual lexicon induction by aligning independently trained word embeddings in two languages and using the resulting cross-lingual embeddings to induce word transla…
Bilingual Lexicon InductionLanguage ModelingLanguage ModellingMachine Translation+6Ultrasound tongue imaging for diarization and alignment of child speech therapy sessions
We investigate the automatic processing of child speech therapy sessions using ultrasound visual biofeedback, with a specific focus on complementing acoustic features with ultrasound images of the tongue for the tasks of…
speaker-diarizationSpeaker DiarizationWord AlignmentOn the Word Alignment from Neural Machine Translation
Prior researches suggest that neural machine translation (NMT) captures word alignment through its attention mechanism, however, this paper finds attention may almost fail to capture word alignment for some NMT models. T…
Machine TranslationNMTTranslationWord AlignmentUnsupervised Multilingual Word Embedding with Limited Resources using Neural Language Models
Recently, a variety of unsupervised methods have been proposed that map pre-trained word embeddings of different languages into the same space without any parallel data. These methods aim to find a linear transformation …
Word AlignmentWord EmbeddingsSaliency-driven Word Alignment Interpretation for Neural Machine Translation
Despite their original goal to jointly learn to align and translate, Neural Machine Translation (NMT) models, especially Transformer, are often perceived as not learning interpretable word alignments. In this paper, we s…
Machine TranslationNMTTranslationWord AlignmentLearning Bilingual Word Embeddings Using Lexical Definitions
Bilingual word embeddings, which representlexicons of different languages in a shared em-bedding space, are essential for supporting se-mantic and knowledge transfers in a variety ofcross-lingual NLP tasks. Existing appr…
TranslationWord AlignmentWord EmbeddingsLanguage Learning and Processing in People and Machines
The goal of this tutorial is to bring the fields of computational linguistics and computational cognitive science closer: we will introduce different stages of language acquisition and their parallel problems in NLP. As …
Language AcquisitionMachine TranslationTranslationWord AlignmentPhonetically-Oriented Word Error Alignment for Speech Recognition Error Analysis in Speech Translation
We propose a variation to the commonly used Word Error Rate (WER) metric for speech recognition evaluation which incorporates the alignment of phonemes, in the absence of time boundary information. After computing the Le…
speech-recognitionSpeech RecognitionTranslationWord AlignmentBootstrapping Method for Developing Part-of-Speech Tagged Corpus in Low Resource Languages Tagset - A Focus on an African Igbo
Most languages, especially in Africa, have fewer or no established part-of-speech (POS) tagged corpus. However, POS tagged corpus is essential for natural language processing (NLP) to support advanced researches such as …
Machine TranslationPOSPOS Taggingspeech-recognition+2Adding Interpretable Attention to Neural Translation Models Improves Word Alignment
Multi-layer models with multiple attention heads per layer provide superior translation quality compared to simpler and shallower models, but determining what source context is most relevant to each target word is more c…
Machine TranslationTranslationWord AlignmentPD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation Projection
We consider unsupervised cross-lingual transfer on two tasks, viz., sentence-level argumentation mining and standard POS tagging. We combine direct transfer using bilingual embeddings with annotation projection, which pr…
Argument MiningCross-Lingual TransferMulti-Task LearningPOS+3Aligning Very Small Parallel Corpora Using Cross-Lingual Word Embeddings and a Monogamy Objective
Count-based word alignment methods, such as the IBM models or fast-align, struggle on very small parallel corpora. We therefore present an alternative approach based on cross-lingual word embeddings (CLWEs), which are tr…
Cross-Lingual Word EmbeddingsWord AlignmentWord EmbeddingsAn Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation
Recent work has shown that the encoder-decoder attention mechanisms in neural machine translation (NMT) are different from the word alignment in statistical machine translation. In this paper, we focus on analyzing encod…
DecoderMachine TranslationNMTTranslation+2Streaming word similarity mining on the cheap
Accurately and efficiently estimating word similarities from text is fundamental in natural language processing. In this paper, we propose a fast and lightweight method for estimating similarities from streams by explici…
Document ClassificationWord AlignmentWord EmbeddingsWord SimilarityCEA LIST: Processing Low-Resource Languages for CoNLL 2018
In this paper, we describe the system used for our first participation at the CoNLL 2018 shared task. The submitted system largely reused the state of the art parser from CoNLL 2017 (\url{https://github.com/tdozat/Parser…
Word AlignmentWord EmbeddingsDiscourse-Related Language Contrasts in English-Croatian Human and Machine Translation
We present an analysis of a number of coreference phenomena in English-Croatian human and machine translations. The aim is to shed light on the differences in the way these structurally different languages make use of di…
Machine TranslationNMTTranslationWord AlignmentA hybrid pipeline of rules and machine learning to filter web-crawled parallel corpora
A hybrid pipeline comprising rules and machine learning is used to filter a noisy web English-German parallel corpus for the Parallel Corpus Filtering task. The core of the pipeline is a module based on the logistic regr…
BIG-bench Machine LearningMachine TranslationregressionTranslation+1Alibaba Submission to the WMT18 Parallel Corpus Filtering Task
This paper describes the Alibaba Machine Translation Group submissions to the WMT 2018 Shared Task on Parallel Corpus Filtering. While evaluating the quality of the parallel corpus, the three characteristics of the corpu…
DiversityMachine TranslationSentenceTranslation+1