ACM Transactions on Asian and Low-Resource Language Information Processing

This article presents our effort in developing a Maithili Part of Speech (POS) tagger. Substantial effort has been devoted to developing POS taggers in several Indian languages, including Hindi, Bengali, Tamil, Telugu, Kannada, Punjabi, and Marathi; but ...

Dense image captioning is a task that requires generating localized captions in natural language for multiple regions of an image. This task leverages its functionalities from both computer vision for recognizing regions in an image and natural language ...

Most existing event extraction works mainly focus on extracting events from one sentence. However, in real-world applications, arguments of one event may scatter across sentences and multiple events may co-occur in one document. Thus, these scenarios ...

Named entity recognition has been one of the most widely researched natural language processing technologies over the past two decades. For the South African languages, however, relatively little research and development work has been done. This changed ...

Building computational resources and tools for the under-resourced languages is strenuous for any Natural Language Processing task. This article presents the first dependency parser for an under-resourced Indian language, Nepali. A prerequisite for ...

End-to-end data-driven approaches lead to rapid development of language generation and dialogue systems. Despite the need for large amounts of well-organized data, these approaches jointly learn multiple components of the traditional generation pipeline ...

Transliterating the text of a language to a foreign script is called forward transliteration and transliterating the text back to the original script is called backward transliteration. In this work, we perform both forward as well as backward ...

In this work we analyze the lyrics of one of the most famous and influential Arab artists in the twentieth century, namely, (Abdel ElHalim Hafez). Lyrics analysis provides a deep insight into the artist’s career evolution and his interactions with the ...

Stance detection aims to assign a stance label (in favor or against) to a post towards a specific target. In the literature, there are many studies focusing on this topic, and most of them treat stance detection as a supervised learning task. Therefore, a ...

People with speech disorders often communicate through special gestures and sign language gestures. However, other people around them might not understand the meaning of those gestures. The research described in this article is aimed at providing an ...

Multilingual NMT has developed rapidly, but still has performance degradation caused by language diversity and model capacity constraints. To achieve the competitive accuracy of multilingual translation despite such limitations, knowledge distillation, ...

Although existing machine reading comprehension models are making rapid progress on many datasets, they are far from robust. In this article, we propose an understanding-oriented machine reading comprehension model to address three kinds of robustness ...

Stress is the property of a language to exhibit prominence or distinction in one or more syllables in a given domain. The existence of word stress has not been suitably explored in previous acoustic studies of the Mizo language, which is a tonal language ...

Sentence ordering aims at restoring orders of shuffled sentences in a paragraph. Previous methods usually predict orders in a single direction, i.e., from head to tail. However, unidirectional prediction inevitably causes error accumulation, which ...

Lack of annotated data is a major concern in Event Detection (ED) tasks for low-resource languages. Cross-lingual ED seeks to address this issue by transferring information across various languages to improve overall performance. In this article, we ...

Natural Language Processing (NLP) has been in practice for the past couple of decades, and extensive work has been done for the Western languages, particularly the English language. The Eastern counterpart, especially the languages of the Indian ...

Emotion detection is a widely studied topic in natural language processing due to its significance in a number of application areas. A plethora of studies have been conducted on emotion detection in European as well as Asian languages. However, a large ...

By leveraging self-supervised tasks, pre-trained language model (PLM) has made significant progress in the field of machine reading comprehension (MRC). However, in classical Chinese MRC (CCMRC), the passage is typically in classical style, but the ...

Relation classification (sometimes called relation extraction) requires trustworthy datasets for fine-tuning large language models, as well as for evaluation. Data collection is challenging for Indian languages, because they are syntactically and ...

Automatic text summarization is a popular area in Natural Language Processing and Machine Learning. In this work, we adopt a graph-based text summarization approach, using PageRank algorithm, for automatically summarizing Konkani text documents. Konkani ...

To achieve effective dialogue processing, the kinds of daily conversations people have must be clarified. Unfortunately, the characteristics of everyday conversations remain insufficiently investigated. In recent years, the Corpus of Everyday Japanese ...

Automatic source code summarization system aims to generate a valuable natural language description for a program, which can facilitate software development and maintenance, code categorization, and retrieval. However, previous sequence-based research did ...

Predicting what happens next in text plays a critical role in building NLP applications. Many methods including count-based and neural-network-based have been proposed to tackle the task called script event prediction: predicting the most suitable ...

Today, comments can be made on many topics on web platforms with the development of the internet. Analyzing the data of these comments is essential for companies and data scientists. There are many methods for analyzing data. Recently, language models ...

In this paper, we propose a novel Low-Power Feature-Attention Chinese Keyword Spotting Framework based on a depthwise separable convolution neural network (DSCNN) with distillation learning to recognize speech signals of Chinese wake-up words. The ...

Despite the impressive success of sequence to sequence models for generative question answering, they need a vast amount of question-answer pairs during training, which is hard and expensive to obtain, especially for low-resource languages. In this ...

In recent years, the use of distributed representations has been a fundamental technology for natural language processing. However, Japanese has multiple compound words, and often we must compare the meanings of a word and a compound word. Moreover, word ...

Over the past few years, researchers are showing huge interest in sentiment analysis and summarization of documents. The primary reason being that huge volumes of information are available in textual format, and this data has proven helpful for real-world ...

Text-to-speech (TTS) synthesis is an active area of research to generate synthetic speech from the underlying text. Compared to English and many European languages, TTS is yet to mature in Malayalam, the principal language of the South Indian state of ...

On social networking sites, online hate speech has become more prevalent due to the quick expansion of mobile computing and Web technology. Previous research has found that being exposed to Internet hate speech has substantial offline implications for ...