Papers Word Alignment

USAAR: An Operation Sequential Model for Automatic Statistical Post-Editing

Bilingual Embeddings and Word Alignments for Translation Quality Estimation

Neural Name Translation Improves Neural Machine Translation

In order to control computational complexity, neural machine translation (NMT) systems convert all rare words outside the vocabulary into a single unk symbol. Previous solution (Luong et al., 2015) resorts to use multipl…

Guided Alignment Training for Topic-Aware Neural Machine Translation

In this paper, we propose an effective way for biasing the attention mechanism of a sequence-to-sequence neural machine translation (NMT) model towards the well-studied statistical word alignment models. We show that our…

Neural Network-based Word Alignment through Score Aggregation

We present a simple neural network for word alignment that builds source and target word window representations to compute alignment scores for sentence pairs. To enable unsupervised training, we use an aggregation opera…

An Attentional Model for Speech Translation Without Transcription

BIRA: Improved Predictive Exchange Word Clustering

Retrofitting Sense-Specific Word Vectors Using Parallel Text

Scaling Up Word Clustering

USFD at SemEval-2016 Task 1: Putting different State-of-the-Arts into a Box

ECNU at SemEval-2016 Task 1: Leveraging Word Embedding From Macro and Micro Views to Boost Performance for Semantic Textual Similarity

WOLVESAAR at SemEval-2016 Task 1: Replicating the Success of Monolingual Word Alignment and Neural Embeddings for Semantic Textual Similarity

ISCAS\_NLP at SemEval-2016 Task 1: Sentence Similarity Based on Support Vector Regression using Multiple Features

RICOH at SemEval-2016 Task 1: IR-based Semantic Textual Similarity Estimation

SimiHawk at SemEval-2016 Task 1: A Deep Ensemble System for Semantic Textual Similarity

IISCNLP at SemEval-2016 Task 2: Interpretable STS with ILP based Multiple Chunk Aligner

UWB at SemEval-2016 Task 2: Interpretable Semantic Textual Similarity with Distributional Semantics for Chunks

Cross-lingual alignment transfer: a chicken-and-egg story?

Deep API Learning

Developers often wonder how to implement a certain functionality (e.g., how to parse XML files) using APIs. Obtaining an API usage sequence based on an API-related natural language query is very helpful in this regard. G…

Capturing divergence in dependency trees to improve syntactic projection

Obtaining syntactic parses is a crucial part of many NLP pipelines. However, most of the world's languages do not have large amounts of syntactically annotated corpora available for building parsers. Syntactic projection…