Pearson Correlation

In this paper, we present a feature-based me- thod to align documents with similar content across two sets of bilingual comparable cor- pora from daily news texts. We evaluate the …...

This paper focuses on identifying, extracting and evaluating features related to syntactic complexity of spontaneous spoken responses as part of an effort to expand the current feature set of an …...

State-of-the-art statistical machine translation (MT) systems have made significant progress towards producing user-acceptable translation output. However, there is still no efficient way for MT systems to inform users which words …...

In this paper we describe the three approaches we submitted to the Semantic Textual Similar- ity task of SemEval 2012. The first approach considers to calculate the semantic similar- ity …...

Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. This paper presents the results of the STS pilot task in Semeval. The training data contained 2000 …...

The Semantic Textual Similarity (STS) shared task (Agirre et al., 2012) computes the degree of semantic equivalence between two sen- tences.1 We show that a simple unsupervised latent semantics based …...

This paper presents the system SSMT measuring the semantic similarity between a paragraph and a sentence submitted to the SemEval 2014 task3: Cross-level Se- mantic Similarity. The special difficulty of …...

This paper presents the system submit- ted by University of Wolverhampton for SemEval-2014 task 1. We proposed a ma- chine learning approach which is based on features extracted using Typed …...

We explore using recursive autoencoders for SemEval 2015 Task 1: Paraphrase and Seman- tic Similarity in Twitter. Our paraphrase de- tection system makes use of phrase-structure parse tree embeddings that …...

Semantic text similarity (STS) is an essential problem in many Natural Language Pro- cessing tasks, which has drawn a considerable amount of attention by research community in recent years. In …...

Quality estimation evaluation commonly takes the form of measurement of the error that exists between predictions and gold standard labels for a particular test set of translations. Issues can arise …...

Paraphrase recognition is the task of iden- tifying whether two pieces of natural lan- guage represent similar meanings. This pa- per describes a system participating in the shared task 1 …...

This paper presents an approach for estimat- ing the Semantic Textual Similarity of full English sentences as specified in Shared Task 2 of SemEval-2015. The semantic similarity of sentence pairs …...

We present a matrix factorization model for learning cross-lingual representations for sentences. Using sentence-aligned corpora, the proposed model learns distributed repre- sentations by factoring the given data into language-dependent factors …...

This paper describes our system developed for English Monolingual subtask (STS Core) of SemEval-2016 Task 1: “Semantic Textual Similarity: A Unified Framework for Seman- tic Processing and Evaluation”. We measure …...

This paper describes the SimiHawk system submission from UMass Lowell for the core Semantic Textual Similarity task at SemEval- 2016. We built four systems: a small feature- based system that …...

AbstractSemantic Textual Similarity (STS) is a foundational NLP task and can be used in a wide range of tasks. To determine the STS of two texts, hundreds of different STS …...

We present our UWB system for Seman- tic Textual Similarity (STS) task at SemEval 2016. Given two sentences, the system esti- mates the degree of their semantic similarity. We use …...

AbstractTo address semantic similarity on multilingual and cross-lingual sentences, we firstly translate other foreign languages into English, and then feed our monolingual English system with various interactive features. Our system …...

AbstractThis article describes our proposed system named LIM-LIG. This system is designed for SemEval 2017 Task1: Semantic Textual Similarity (Track1). LIM-LIG proposes an innovative enhancement to word embedding-based model devoted …...

AbstractTranslation quality estimation is a task of growing importance in NLP, due to its potential to reduce post-editing human effort in disruptive ways. However, this potential is currently limited by …...

AbstractThis paper reports the details of our submissions in the task 1 of SemEval 2017. This task aims at assessing the semantic textual similarity of two sentences or texts. We …...

AbstractThis paper shows the details of our system submissions in the task 2 of SemEval 2017. We take part in the subtask 1 of this task, which is an English …...

AbstractThis paper describes the model UdL we proposed to solve the semantic textual similarity task of SemEval 2017 workshop. The track we participated in was estimating the semantics relatedness of …...

AbstractWhile sentiment and emotion analysis has received a considerable amount of research attention, the notion of understanding and detecting the intensity of emotions is relatively less explored. This paper describes …...

AbstractSocial media based micro-blogging sites like Twitter have become a common source of real-time information (impacting organizations and their strategies, and are used for expressing emotions and opinions. Automated analysis …...

The production of speech corpora typically involves manual labor to verify and correct the output of automatic transcription/segmentation processes. This study investigates the possibility of speeding up this correction process …...

AbstractTraditional sentiment analysis approaches mainly focus on classifying the sentiment polarities or emotion categories of texts. However, they can’t exploit the sentiment intensity information. Therefore, the SemEval-2018 Task 1 is …...

AbstractDue to the ubiquitous use of embeddings as input representations for a wide range of natural language tasks, imputation of embeddings for rare and unseen words is a critical problem …...

AbstractAutomatically evaluating dialogue coherence is a challenging but high-demand ability for developing high-quality open-domain dialogue systems. However, current evaluation metrics consider only surface features or utterance-level semantics, without explicitly considering …...

AbstractLexical ambiguity is widespread in language, allowing for the reuse of economical word forms and therefore making language more efficient. If ambiguous words cannot be disambiguated from context, however, this …...

AbstractWith the increasing popularity of learning Chinese as a second language (L2) the development of an automatic essay scoring (AES) method specially for Chinese L2 essays has become animportant task. …...

AbstractThe main contribution of this paper is to fine-tune transformer-based language models pre-trained on several text corpora, some being general (E.g., Wikipedia, BooksCorpus), some being the corpora from which the …...

AbstractQuality Estimation (QE) is an important component of the machine translation workflow as it assesses the quality of the translated output without consulting reference translations. In this paper, we discuss …...

AbstractThis paper describes our submission to SemEval-2021 Task 1: predicting the complexity score for single words. Our model leverages standard morphosyntactic and frequency-based features that proved helpful for Complex Word …...

AbstractThe present work aims at assigning a complexity score between 0 and 1 to a target word or phrase in a given sentence. For each Single Word Target, a Random …...

AbstractWe present two convolutional neural networks for predicting the complexity of words and phrases in context on a continuous scale. Both models utilize word and character embeddings alongside lexical features …...

AbstractThis paper describes our submission to the WMT2021 shared metrics task. Our metric is operative to segment-level and system-level translations. Our belief toward a better metric is to detect a …...

This paper investigates automatic assessments of text readability for second language learn- ers. The goodness of text readability as- sessment methods has been evaluated using the correlation coefficients between their …...

AbstractThis paper presents our system for document-level semantic textual similarity (STS) evaluation at SemEval-2022 Task 8: “Multilingual News Article Similarity”. The semantic information used is obtained by using different semantic …...

Document Clustering aims to group similar documents based on the distance among them. A wide range of distance measures are available in the literature, and selecting an appropriate distance function …...

AbstractTraining with noisy labelled data is known to be detrimental to model performance, especially for high-capacity neural network models in low-resource domains. Our experiments suggest that standard regularisation strategies, such …...

AbstractThis paper describes the submission of UZH_CLyp for the SemEval 2023 Task 9 “Multilingual Tweet Intimacy Analysis. We achieved second-best results in all 10 languages according to the official Pearson’s …...