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Linguistics

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The Emotion Probe: On the Universality of Cross-Linguistic and Cross-Gender Speech Emotion Recognition via Machine Learning.

Sensors (Basel, Switzerland)
Machine Learning (ML) algorithms within a human-computer framework are the leading force in speech emotion recognition (SER). However, few studies explore cross-corpora aspects of SER; this work aims to explore the feasibility and characteristics of ...

Towards more patient friendly clinical notes through language models and ontologies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Clinical notes are an efficient way to record patient information but are notoriously hard to decipher for non-experts. Automatically simplifying medical text can empower patients with valuable information about their health, while saving clinicians ...

Dynamic Invariant-Specific Representation Fusion Network for Multimodal Sentiment Analysis.

Computational intelligence and neuroscience
Multimodal sentiment analysis (MSA) aims to infer emotions from linguistic, auditory, and visual sequences. Multimodal information representation method and fusion technology are keys to MSA. However, the problem of difficulty in fully obtaining hete...

Intelligent Error Correction of College English Spoken Grammar Based on the GA-MLP-NN Algorithm.

Computational intelligence and neuroscience
With the development of neural networks in deep learning, artificial intelligence machine learning has become the main focus of researchers. In College English grammar detection, oral grammar is the most error rate content. So, this paper optimizes M...

Event parsing and the origins of grammar.

Wiley interdisciplinary reviews. Cognitive science
How did grammar evolve? Perhaps a better way to ask the question is what kind of cognition is needed to enable grammar. The present analysis departs from the observation that linguistic communication is structured in terms of agents and patients, a r...

Unsupervised cross-lingual model transfer for named entity recognition with contextualized word representations.

PloS one
Named entity recognition (NER) is one fundamental task in the natural language processing (NLP) community. Supervised neural network models based on contextualized word representations can achieve highly-competitive performance, which requires a larg...

English Grammar Detection Based on LSTM-CRF Machine Learning Model.

Computational intelligence and neuroscience
Deep learning and neural network have been widely used in the field of speech, vocabulary, text, pictures, and other information processing fields, which has achieved excellent research results. Neural network algorithm and prediction model were used...

A novel approach for the analysis of time-course gene expression data based on computing with words.

Journal of biomedical informatics
In this paper, a novel approach is proposed for the analysis of time-course gene expression data based on the path-breaking work of Zadeh, Computing with Words. This method can automatically discover the patterns of temporal gene expression profile i...

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...