Articles

Automatic semantic annotation of natural language data is an important task in Natural Language Processing, and a variety of semantic taggers have been developed for this task, particularly for English. However, for many languages, particularly for low-resource languages, such tools are yet to be developed. In this paper, we report …...

Distributional hypothesis has been playing a central role in statistical NLP. Recently, however, its limitation in incorporating perceptual and empirical knowledge is noted, eliciting a field of perceptually grounded computational semantics. Typical sources of features in such a research are image datasets, where images are accompanied by linguistic tags and/or …...

Multi-sense word embedding is an important extension of neural word embeddings. By leveraging context of each word instance, multi-prototype version of word embeddings were accomplished to represent the multi-senses. Unfortunately, this kind of context based approach inevitably produces multiple senses which should actually be a single one, suffering from the …...

An evaluation of distributed word representation is generally conducted using a word similarity task and/or a word analogy task. There are many datasets readily available for these tasks in English. However, evaluating distributed representation in languages that do not have such resources (e.g., Japanese) is difficult. Therefore, as a first …...

In this paper, we present the first analysis of bottom-up manual semantic clustering of verbs in three languages, English, Polish and Croatian. Verb classes including syntactic and semantic information have been shown to support many NLP tasks by allowing abstraction from individual words and thereby alleviating data sparseness. The availability …...

Users often query a search engine with a specific question in mind and often these queries are keywords or sub-sentential fragments. In this paper, we are proposing a method to generate well-formed natural language question from a given keyword-based query, which has the same question intent as the query.Conversion of …...

Much work has been done on machine translation between major language pairs including Arabic–English and English–Japanese thanks to the availability of large-scale parallel corpora with manually verified subsets of parallel sentences. However, there has been little research conducted on the Arabic–Japanese language pair due to its parallel-data scarcity, despite being …...

Transliteration from low-resource languages is difficult, in large part due to the small amounts of data available for training transliteration systems. In this paper, we evaluate the effectiveness of several translation methods in the task of transliterating around 1000 Bible names from 591 languages into English. In this extremely low-resource …...

Neural Machine Translation (NMT) has been widely used in recent years with significant improvements for many language pairs. Although state-of-the-art NMT systems are generating progressively better translations, idiom translation remains one of the open challenges in this field. Idioms, a category of multiword expressions, are an interesting language phenomenon where …...

Neural machine translation (NMT) becomes a new state of the art and achieves promising translation performance using a simple encoder-decoder neural network. This neural network is trained once on the parallel corpus and the fixed network is used to translate all the test sentences. We argue that the general fixed …...

The past several years have witnessed the rapid progress of end-to-end Neural Machine Translation (NMT). However, there exists discrepancy between training and inference in NMT when decoding, which may lead to serious problems since the model might be in a part of the state space it has never seen during …...

In machine translation, we often try to collect resources to improve performance. However, most of the language pairs, such as Korean-Arabic and Korean-Vietnamese, do not have enough resources to train machine translation systems. In this paper, we propose the use of synthetic methods for extending a low-resource corpus and apply …...

Neural Machine Translation (NMT) has drawn much attention due to its promising translation performance in recent years. However, the under-translation and over-translation problem still remain a big challenge. Through error analysis, we find that under-translation is much more prevalent than over-translation and the source words that need to be reordered …...

In several areas of NLP evaluation, test suites have been used to analyze the strengths and weaknesses of systems. Today, Machine Translation (MT) quality is usually assessed by shallow automatic comparisons of MT outputs with reference corpora resulting in a number. Especially the trend towards neural MT has renewed peoples’ …...

This paper introduces EFLLex, an innovative lexical resource that describes the use of 15,280 English words in pedagogical materials across the proficiency levels of the European Framework of Reference for Languages. The methodology adopted to produce the resource implies the selection of an efficient part-of-speech tagger, the use of a …...

Current publicly available Chinese FrameNet has a relatively low coverage of frames and lexical units compared with FrameNet in other languages. Frames are incompletely specified for some lexical units, and some critical lexical elements are even missing. That results in suitable frames cannot be triggered and filled in practical applications. …...

Neural Machine Translation (NMT) has attracted increasing attention in the recent years. However, it tends to require very large training corpora which could prove problematic for languages with low resources. For this reason, Statistical Machine Translation (SMT) continues to be a popular approach for low-resource language pairs. In this work, …...

Building language resources for endangered languages, especially in the case of dictionaries, requires a substantial amount of manual work. This, however, is a time-consuming undertaking, and it is also why we propose an automated method for expanding the knowledge in the existing dictionaries. In this paper, we present an approach …...

A major issue in machine translation (MT) applications is the recognition and translation of named entities. This is especially true for Chinese and Japanese, whose scripts present linguistic and algorithmic challenges not found in other languages. This paper discusses some of the major issues in Japanese and Chinese MT, such …...

This paper presents the structure, features and design of a new interlinked verbal synonym lexical resource called CzEngClass and the editor tool being developed to assist the work. This lexicon captures cross-lingual (Czech and English) synonyms, using valency behavior of synonymous verbs in relation to semantic roles as one of …...