Articles

Community Question Answering (CQA) websites have become a very popular and useful source of information, which helps users to find out answers to their corresponding questions. On one hand, if a user’s question does not exist in the forum, a new post is created so that other users can contribute …...

Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, existing reading comprehension datasets are mostly in English. To add diversity in reading comprehension datasets, in this paper we propose a new Chinese reading comprehension dataset for accelerating related research in the community. …...

Recent years have witnessed a high interest in non-factoid question answering using Community Question Answering (CQA) web sites. Despite ongoing research using state-of-the-art methods, there is a scarcity of available datasets for this task. Why-questions, which play an important role in open-domain and domain-specific applications, are difficult to answer automatically …...

In this paper we present the Konstanz Resource of Questions (KRoQ), the first dependency-parsed, parallel multilingual corpus of information-seeking and non-information-seeking questions. In creating the corpus, we employ a linguistically motivated rule-based system that uses linguistic cues from one language to help classify and annotate questions across other languages. Our …...

Epitran is a massively multilingual, multiple back-end system for G2P (grapheme-to-phoneme) transduction which is distributed with support for 61 languages. It takes word tokens in the orthography of a language and outputs a phonemic representation in either IPA or X-SAMPA. The main system is written in Python and is publicly …...

A standard ASR system is built using three types of mutually related language resources: apart from speech recordings and orthographic transcripts, a pronunciation component maps tokens in the transcripts to their phonetic representations. Its implementation is either lexicon-based (whether by way of simple lookup or of a stochastic grapheme-to-phoneme converter …...

The modeling of psycholinguistic phenomena, such as word reading, with machine learning techniques requires the featurization of word stimuli into appropriate orthographic and phonological representations. Critically, the choice of features impacts the performance of machine learning algorithms, and can have important ramifications for the conclusions drawn from a model. As …...

There is an increasing demand for multilingual sentiment analysis, and most work on sentiment lexicons is still carried out based on English lexicons like WordNet. In addition, many of the non-English sentiment lexicons that do exist have been compiled by (machine) translation from English resources, thereby arguably obscuring possible language-specific …...

In this paper, we present a student course feedback corpus, a novel resource for opinion target extraction and sentiment analysis. The corpus is developed with the main aim of summarizing general feedback given by students on undergraduate-level courses. In this corpus, opinion targets, opinion expressions, and polarities of the opinion …...

Past work in computational sarcasm deals primarily with sarcasm detection. In this paper, we introduce a novel, related problem: sarcasm target identification (i.e., extracting the target of ridicule in a sarcastic sentence). As a benchmark, we introduce a new dataset for the task. This dataset is manually annotated for the …...

The way information spreads through society has changed significantly over the past decade with the advent of online social networking. Twitter, one of the most widely used social networking websites, is known as the real-time, public microblogging network where news breaks first. Most users love it for its iconic 140-character …...

Today customers voice attitudes, opinions and their experience about some brands, companies, products or services through center calls, web reviews or SNS and analyzing them is an important task. On the other hand, customer loyalty has long been a topic of high interest in both academia and industry. Therefore, it …...

Aspect Based Sentiment Analysis (ABSA) aims at collecting detailed opinion information according to products and their features, via the recognition of targets of the opinions in text. Though some annotated data have been produced in challenges as SemEval, resources are still scarce, especially for languages other than English. We are …...

We present Lingmotif-lex, a new, wide-coverage, domain-neutral lexicon for sentiment analysis in English. We describe the creation process of this resource, its assumptions, format, and valence system. Unlike most sentiment lexicons currently available, Lingmotif-lex places strong emphasis on multi-word expressions, and has been manually curated to be as accurate, unambiguous, …...

This paper introduces the three SSIX corpora for sentiment analysis. These corpora address the need to provide annotated data for supervised learning methods. They focus on stock-market related messages extracted from two financial microblog platforms, i.e., StockTwits and Twitter. In total they include 2,886 messages with opinion targets. These messages …...

St. Lawrence Island / Central Siberian Yupik is an endangered language, indigenous to St. Lawrence Island in Alaska and the Chukotka Peninsula of Russia, that exhibits pervasive agglutinative and polysynthetic properties. This paper discusses an implementation of a finite-state morphological analyzer for Yupik that was developed in accordance with the …...

In this paper, we introduce MADARi, a joint morphological annotation and spelling correction system for texts in Standard and Dialectal Arabic. The MADARi framework provides intuitive interfaces for annotating text and managing the annotation process of a large number of sizable documents. Morphological annotation includes indicating, for a word, in …...

In this paper we present the annotation scheme and parser results of the animacy feature in Russian and Arabic, two morphologically- rich languages, in the spirit of the universal dependency framework (McDonald et al., 2013; de Marneffe et al., 2014). We explain the animacy hierarchies in both languages and make …...

Statistical Machine Translation (SMT) approaches fails to handle the rich morphology when translating into morphologically rich language. This is due to the data sparsity, which is the missing of the morphologically inflected forms of words from the parallel corpus. We investigated a method to generate these unseen morphological forms. In …...

is paper describes a finite-state approach to morphological analysis and generation of Gagauz, a Turkic language spoken in the Republic of Moldova. Finite-state approaches are commonly used in morphological modelling, but one of the novelties of our approach is that we explicitly handle orthographic errors and variance, in addition to …...