Papers Word Alignment

Log-linear Models for Uyghur Segmentation in Spoken Language Translation

To alleviate data sparsity in spoken Uyghur machine translation, we proposed a log-linear based morphological segmentation approach. Instead of learning model only from monolingual annotated corpus, this approach optimiz…

DT\_Team at SemEval-2017 Task 1: Semantic Similarity Using Alignments, Sentence-Level Embeddings and Gaussian Mixture Model Output

We describe our system (DT Team) submitted at SemEval-2017 Task 1, Semantic Textual Similarity (STS) challenge for English (Track 5). We developed three different models with various features including similarity scores …

STS-UHH at SemEval-2017 Task 1: Scoring Semantic Textual Similarity Using Supervised and Unsupervised Ensemble

This paper reports the STS-UHH participation in the SemEval 2017 shared Task 1 of Semantic Textual Similarity (STS). Overall, we submitted 3 runs covering monolingual and cross-lingual STS tracks. Our participation invol…

LIPN-IIMAS at SemEval-2017 Task 1: Subword Embeddings, Attention Recurrent Neural Networks and Cross Word Alignment for Semantic Textual Similarity

In this paper we report our attempt to use, on the one hand, state-of-the-art neural approaches that are proposed to measure Semantic Textual Similarity (STS). On the other hand, we propose an unsupervised cross-word ali…

Improving Discourse Relation Projection to Build Discourse Annotated Corpora

The naive approach to annotation projection is not effective to project discourse annotations from one language to another because implicit discourse relations are often changed to explicit ones and vice-versa in the tra…

Incorporating Word Reordering Knowledge into Attention-based Neural Machine Translation

This paper proposes three distortion models to explicitly incorporate the word reordering knowledge into attention-based Neural Machine Translation (NMT) for further improving translation performance. Our proposed models…

Hybrid Neural Network Alignment and Lexicon Model in Direct HMM for Statistical Machine Translation

Recently, the neural machine translation systems showed their promising performance and surpassed the phrase-based systems for most translation tasks. Retreating into conventional concepts machine translation while utili…

Six Challenges for Neural Machine Translation

We explore six challenges for neural machine translation: domain mismatch, amount of training data, rare words, long sentences, word alignment, and beam search. We show both deficiencies and improvements over the quality…

Multilingwis\mbox$^2$ -- Explore Your Parallel Corpus

Exploring Properties of Intralingual and Interlingual Association Measures Visually

Crossing the border twice: Reimporting prepositions to alleviate L1-specific transfer errors

Word-Alignment-Based Segment-Level Machine Translation Evaluation using Word Embeddings

One of the most important problems in machine translation (MT) evaluation is to evaluate the similarity between translation hypotheses with different surface forms from the reference, especially at the segment level. We …

Addressing Problems across Linguistic Levels in SMT: Combining Approaches to Model Morphology, Syntax and Lexical Choice

Many errors in phrase-based SMT can be attributed to problems on three linguistic levels: morphological complexity in the target language, structural differences and lexical choice. We explore combinations of linguistica…

A Web-Based Interactive Tool for Creating, Inspecting, Editing, and Publishing Etymological Datasets

The paper presents the Etymological DICtionary ediTOR (EDICTOR), a free, interactive, web-based tool designed to aid historical linguists in creating, editing, analysing, and publishing etymological datasets. The EDICTOR…

Computational analysis of Gondi dialects

This paper presents a computational analysis of Gondi dialects spoken in central India. We present a digitized data set of the dialect area, and analyze the data using different techniques from dialectometry, deep learni…

Slavic Forest, Norwegian Wood

We once had a corp, or should we say, it once had us They showed us its tags, isn{'}t it great, unified tags They asked us to parse and they told us to use everything So we looked around and we noticed there was near not…

CORBON 2017 Shared Task: Projection-Based Coreference Resolution

The CORBON 2017 Shared Task, organised as part of the Coreference Resolution Beyond OntoNotes workshop at EACL 2017, presented a new challenge for multilingual coreference resolution: we offer a projection-based setting …

Discovering Light Verb Constructions and their Translations from Parallel Corpora without Word Alignment

We propose a method for joint unsupervised discovery of multiword expressions (MWEs) and their translations from parallel corpora. First, we apply independent monolingual MWE extraction in source and target languages sim…

Show Me Your Variance and I Tell You Who You Are - Deriving Compound Compositionality from Word Alignments

We use word alignment variance as an indicator for the non-compositionality of German and English noun compounds. Our work-in-progress results are on their own not competitive with state-of-the art approaches, but they s…

Neural Networks for Negation Cue Detection in Chinese

Negation cue detection involves identifying the span inherently expressing negation in a negative sentence. In Chinese, negative cue detection is complicated by morphological proprieties of the language. Previous work ha…