ACM Transactions on Asian and Low-Resource Language Information Processing

How to utilize information sufficiently is a key problem in neural machine translation (NMT), which is effectively improved in rich-resource NMT by leveraging large-scale bilingual sentence pairs. However, for low-resource NMT, lack of bilingual ...

Machine reading comprehension question answering (MRC-QA) is the task of understanding the context of a given passage to find a correct answer within it. A passage is composed of several sentences; therefore, the length of the input sentence becomes ...

Authorship identification helps to identify the true author of a given anonymous document from a set of candidate authors. The applications of this task can be found in several domains, such as law enforcement agencies and information retrieval. These ...

There has been growing interest among researchers in quality estimation (QE), which attempts to automatically predict the quality of machine translation (MT) outputs. Most existing works on QE are based on supervised approaches using quality-annotated ...

A method of learning and modeling unit embeddings using deep neutral networks (DNNs) is presented in this article for unit-selection-based Mandarin speech synthesis. Here, a unit embedding is defined as a fixed-length embedding vector for a phone-sized ...

In this article, we present an automatic semantic role labeling system in Persian consisting of two modules: argument identification for specifying argument spans and argument classification for categorizing their semantic roles. Our modules have been ...

A 20,000-sentence Burmese (Myanmar) treebank on news articles has been released under a CC BY-NC-SA license. Complete phrase structure annotation was developed for each sentence from the morphologically annotated data prepared in previous work of Ding ...

Two major problems of Korean part-of-speech (POS) tagging are that the word-spacing unit is not mapped one-to-one to a POS tag and that morphemes should be recovered during POS tagging. Therefore, this article proposes a novel two-step Korean POS tagger ...

In Neural Machine Translation (NMT), due to the limitations of the vocabulary, unknown words cannot be translated properly, which brings suboptimal performance of the translation system. For resource-scarce NMT that have small-scale training corpus, the ...

Bilingual resources play a very important role in many natural language processing tasks, especially the tasks in cross-lingual scenarios. However, it is expensive and time consuming to build such resources. Lexical borrowing happens in almost every ...

In neural machine translation (NMT), the source and target words are at the two ends of a large deep neural network, normally mediated by a series of non-linear activations. The problem with such consequent non-linear activations is that they ...

Today, the knowledge base question answering (KB-QA) system is promising to achieve a large-scale high-quality reply in the e-commerce industry. However, there exist two major challenges to efficiently support large-scale KB-QA systems. On the one hand, ...

The primary task of extractive summarization is to automatically select a set of representative sentences from a text or spoken document that can concisely express the most important theme of the original document. Recently, language modeling (LM) has ...

This article proposes to conduct natural language inference with novel Enhanced-Relation-Head-Dependent triplets (RHD triplets), which are constructed via enhancing each word in the RHD triplet with its associated local context. Most previous approaches ...