ACM Transactions on Asian and Low-Resource Language Information Processing

Text readability assessment is a well-known problem that has acquired even more importance in today’s information-rich world. In this article, we survey various approaches to measuring and assessing the readability of texts. Our specific goal is to ...

Learning response generation models constitute the main component of building open-domain dialogue systems. However, training open-domain response generation models requires large amounts of labeled data and pre-trained language generation models that are ...

With the advances in Natural Language Processing (NLP), the industry has been moving towards human-directed artificial intelligence (AI) solutions. Recently, chatbots and automated news generation have captured a lot of attention. The goal is to ...

Emoji are often used in social media to enrich users’ emotions, and they play an important role in the task of social media sentiment analysis. In practice, researchers are more likely to consider emoji as special symbols and treat them separately from ...

Chinese short text sentiment analysis can help understand society’s views on various hot topics. Many existing sentiment analysis methods are based on sentiment dictionaries. Still, sentiment dictionaries are easily affected by subjective factors. They ...

As a potential bilingual resource, loanwords play a very important role in many natural language processing tasks. If loanwords in a low-resource language can be identified effectively, the generated donor-receipt word pairs will benefit many cross-...

Automatic spoken instruction understanding (SIU) of the controller-pilot conversations in the air traffic control (ATC) requires not only recognizing the words and semantics of the speech but also determining the role of the speaker. However, few of the ...

Multi-view fusion approaches have gained increasing interest in the past few years by researchers. This interest comes due to the many perspectives that datasets can be looked at and evaluated. One of the most urging areas that require constant leveraging ...

Document-level relation extraction (DocRE) aims to extract relations among entities across multiple sentences within a document by using reasoning skills (i.e., pattern recognition, logical reasoning, coreference reasoning, etc.) related to the reasoning ...

Studies on natural language processing are mainly conducted in English, with very few exploring languages that are under-resourced, including the Dravidian languages. We present a novel work in detecting offensive language using a corpus collected from ...

This article tackles the problem of sentiment analysis in the Arabic language where a new deep learning model has been put forward. The proposed model uses a hybrid bidirectional gated recurrent unit (BiGRU) and bidirectional long short-term memory (...

The explosive growth of social media has fueled an extensive increase in online freedom of speech. The worldwide platform of human voice creates possibilities to assail other users without facing any consequences, and flout social etiquettes, resulting in ...

Neural architecture search (NAS) has shown the strong performance of learning neural models automatically in recent years. But most NAS systems are unreliable due to the architecture gap brought by discrete representations of atomic architectures. In this ...

Neural variational inference-based topic modeling has gained great success in mining abstract topics from documents. However, these topic models usually mainly focus on optimizing the topic proportions for documents, while the quality and the internal ...

Recently, the Text-to-SQL task has received much attention. Many sophisticated neural models have been invented that achieve significant results. Most current work assumes that all the inputs are legal and the model should generate an SQL query for any ...

In sequence-to-sequence modeling tasks, such as image captioning, machine translation, and visual question answering, encoder-decoder architectures are state of the art. An encoder, convolutional neural network (CNN) encodes input images into fixed ...

Cyberbullying refers to bullying and harassment of defenseless or vulnerable people such as children, teenagers, and women through any means of communication (e.g., e-mail, text messages, wall posts, tweets) over any online medium (e.g., social media, ...

The Devanagari script is one of the most widely used scripts worldwide. The existing deep learning-based optical character recognition system for printed Devanagari scripts using Convolutional Neural Network – Recurrent Neural Network, or CRNN is not ...

Tokenization is an important text preprocessing step to prepare input tokens for deep language models. WordPiece and BPE are de facto methods employed by important models, such as BERT and GPT. However, the impact of tokenization can be different for ...

Benefiting from the improvement of positional encoding and the introduction of lexical knowledge, Transformer has achieved superior performance than the prevailing BiLSTM-based models in named entity recognition (NER) task. However, existing Transformer-...

As a common language form in oral communication, short text is hard to be used in the applications such as intent understanding, text classification and so on due to its limited content and information, as well as irregular expression and missing ...