ACM Transactions on Asian and Low-Resource Language Information Processing

In today's intelligent age, the vigorous development of education-based information analysis technology has had a profound impact on the education and teaching process. The use of computational linguistics technology to extract teaching data for learning ...

Parallel sentence pairs play a very important role in many natural language processing tasks, especially cross-lingual tasks such as machine translation. So far, many Asian language pairs lack bilingual parallel sentences. As collecting bilingual parallel ...

English has become an utterly crucial device to take part in global verbal exchange and competition. It is essential to enhance English teaching's flexibility to meet the desires to improve the market economy. Therefore, powerful coaching strategies and ...

The handwritten character recognition process has gained significant attention among research communities due to its application in assistive technologies for visually impaired people, human–robot interaction, automated registry for business documents, ...

In recent years, neural networks have achieved impressive performance on dialogue response generation. However, most of these models still suffer from some shortcomings, such as yielding uninformative responses and lacking explainable ability. This ...

World Wide Web (WWW) is playing a vital role for sharing dynamic knowledge in every field of life. The information on web comprises a huge amount of data in different forms such as structured, semi structured, or few is totally in unstructured format. Due ...

‘‘Audiobook” is a multimedia-based reading technology that has emerged in recent years. Realizing the alignment of e-book text and book audio is the most important part of its processing. This article describes an audio and text alignment algorithm using ...

This article proposes an improved Bayesian scheme by focusing on the region in which Bayesian may fail to correctly identify labels and improve classification performance by handling those errors. Bayesian method, as a probabilistic classifier, uses Bayes’...

An ontology is a state-of-the-art knowledge modeling technique in the natural language domain, which has been widely used to overcome the linguistic barriers in Asian and European countries’ intelligent applications. However, due to the different ...

Applying artificial intelligence to Chinese language translation in computational linguistics is of practical significance for economic boosts and cultural exchanges. In the present work, the bi-directional long short-term memory (BiLSTM) network is ...

Identification of the best institute for higher education has become one of the most challenging issues in the present education system. It has become more complicated as more institutes exist with extraordinary infrastructural facilities. Therefore, a ...

Word translation is a natural language processing task that provides translation between the words of a source and a target language. As a task, it reduces to the induction of a bilingual dictionary, which is typically performed by aligning word ...

The sentiment lexicon is an important tool for natural language processing tasks. In addition to being able to determine the sentiment polarity of words or phrases, it can assist attribute-level, sentence-level, and text-level sentiment analysis tasks. In ...

Combining different input modalities beyond text is a key challenge for natural language processing. Previous work has been inconclusive as to the true utility of images as a supplementary information source for text classification tasks, motivating this ...

In recent years, text-independent speaker verification has remained a hot research topic, especially for the limited enrollment and/or test data. At the same time, due to the lack of sufficient training data, the study of low-resource few-shot speaker ...

Punctuation prediction is critical as it can enhance the readability of machine-transcribed speeches or texts significantly by adding appropriate punctuation. Furthermore, systems like Automatic Speech Recognizer (ASR) produce texts that are unpunctuated, ...

In recent years, the Question Answering System (QAS) has been widely used to develop many systems, such as conversation systems, chatbots, and intelligent search. Depending on the amount of information or knowledge that the system processes, the system ...

The semantic word similarity task aims to quantify the degree of similarity between a pair of words. In literature, efforts have been made to create standard evaluation resources to develop, evaluate, and compare various methods for semantic word ...

There has been growing interest in building surface realization systems to support the automatic generation of text in African languages. Such tools focus on converting abstract representations of meaning to a text. Since African languages are low-...

Statistical parametric speech synthesis techniques such as deep neural network (DNN) and hidden Markov model (HMM) have grown in popularity since last decade over the concatenative speech synthesis approaches by modelling excitation and spectral ...

Analyzing real-time news feeds and their impacts in the real world is a complex task in the social networking arena. Particularly, countries with a multilingual environment have various patterns and perceptions of news reports considering the diversity of ...

Building a human-computer conversational system that can communicate with humans is a research hotspot in the field of artificial intelligence. Traditional dialogue systems tend to produce irrelevant and non-information responses, which reduce people’s ...

In recent studies, pre-trained models and pseudo data have been key factors in improving the performance of the English grammatical error correction (GEC) task. However, few studies have examined the role of pre-trained models and pseudo data in the ...

Frame-semantic Parsing (FSP) is a challenging and critical task in Natural Language Processing (NLP). Most of the existing studies decompose the FSP task into frame identification (FI) and frame semantic role labeling (FSRL) subtasks, and adopt a pipeline ...

Chinese Named Entity Recognition (NER) is an essential task in natural language processing, and its performance directly impacts the downstream tasks. The main challenges in Chinese NER are the high dependence of named entities on context and the lack of ...

Success of neural networks in natural language processing has paved the way for neural machine translation (NMT), which rapidly became the mainstream approach in machine translation. Significant improvement in translation performance has been achieved ...