AIMC Topic: Linguistics

Clear Filters Showing 81 to 90 of 189 articles

Negative content in auditory verbal hallucinations: a natural language processing approach.

Cognitive neuropsychiatry
INTRODUCTION: Negative content of auditory verbal hallucinations (AVH) is a strong predictor of distress and impairment. This paper quantifies emotional voice-content in order to explore both subjective (i.e. perceived) and objectively (i.e. linguist...

Designing a hybrid dimension reduction for improving the performance of Amharic news document classification.

PloS one
The volume of Amharic digital documents has grown rapidly in recent years. As a result, automatic document categorization is highly essential. In this paper, we present a novel dimension reduction approach for improving classification accuracy by com...

Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings.

Neural networks : the official journal of the International Neural Network Society
Respiration is an essential and primary mechanism for speech production. We first inhale and then produce speech while exhaling. When we run out of breath, we stop speaking and inhale. Though this process is involuntary, speech production involves a ...

Human cortical encoding of pitch in tonal and non-tonal languages.

Nature communications
Languages can use a common repertoire of vocal sounds to signify distinct meanings. In tonal languages, such as Mandarin Chinese, pitch contours of syllables distinguish one word from another, whereas in non-tonal languages, such as English, pitch is...

Neural Encoding and Decoding With Distributed Sentence Representations.

IEEE transactions on neural networks and learning systems
Building computational models to account for the cortical representation of language plays an important role in understanding the human linguistic system. Recent progress in distributed semantic models (DSMs), especially transformer-based methods, ha...

A Survey of the Usages of Deep Learning for Natural Language Processing.

IEEE transactions on neural networks and learning systems
Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief introduction to the field and a quick overview of deep learning archite...

Pain Treatment Evaluation in COVID-19 Patients with Hesitant Fuzzy Linguistic Multicriteria Decision-Making.

Journal of healthcare engineering
The coronavirus disease 2019 (COVID-19) has emerged as a worldwide pandemic since March 2020. Although most patients complain of moderate or severe pain, these symptoms are generally underestimated and appropriate treatment is not applied. This study...

Artificial Intelligence in mental health and the biases of language based models.

PloS one
BACKGROUND: The rapid integration of Artificial Intelligence (AI) into the healthcare field has occurred with little communication between computer scientists and doctors. The impact of AI on health outcomes and inequalities calls for health professi...

Interactive Dual Attention Network for Text Sentiment Classification.

Computational intelligence and neuroscience
Text sentiment classification is an essential research field of natural language processing. Recently, numerous deep learning-based methods for sentiment classification have been proposed and achieved better performances compared with conventional ma...

Recognition of Non-Manual Content in Continuous Japanese Sign Language.

Sensors (Basel, Switzerland)
The quality of recognition systems for continuous utterances in signed languages could be largely advanced within the last years. However, research efforts often do not address specific linguistic features of signed languages, as e.g., non-manual exp...