Human Computer Interaction for Intelligent Systems

doi:10.3390/books978-3-0365-6576-7

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https://mdpi.com/books/pdfview/book/6751

Contributor(s)

Pleva, Matúš (editor)

Liao, Yuan-Fu (editor)

Bours, Patrick (editor)

Language

English

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Abstract

This reprint addresses the unique opportunities and challenges associated with human–computer interaction with intelligent systems. First, state-of-the-art reviews are presented about speech emotions, automatic spelling correction, and art usage in virtual reality. We encouraged authors to submit reports describing systems built for different languages and multilingual systems. The linguistic, emotional, prosodic, and dialogue aspects of speech communication are investigated. Special attention is given to sentiment and emotional analysis from text and speech. Speech audiometry, offline speech recognition, and text-independent speaker verification systems are elaborated. The rapidly growing domain of virtual reality applications is of interest both as an application domain in which new interfaces and interaction methods are needed and as a potential testbed for evaluating speech and other interface modalities.

URI

https://directory.doabooks.org/handle/20.500.12854/98024

Keywords

pediatric speech audiometry; hearing tests; conditioned play audiometry; human–computer interaction; mechatronic devices; Internet of Things; cyber-physical systems; system control; augmented reality; mixed reality; Azure cloud; sentiment analysis; opinion classification; lexicon-based approach; hybrid approach; lexicon generation; lexicon labelling; particle swarm optimization; spelling correction; natural language processing; diacritization; error model; context model; Natural Language Processing; deep learning; grammar error detection; word embedding; text-independent speaker verification system; self-attentive pooling; multi-layer aggregation; feature recalibration; deep length normalization; speaker embedding; shortcut connections; convolutional neural networks; ResNet; human–robot interaction; dictionary approach; machine learning approach; social robotics; human-robot interaction; mental workload; heart rate variability; machine learning; sentiment level evaluation; handicraft product; 3D handicraft products; smartphone applications; user interaction; user’s attracting attention; question-answering forum; healthcare informatics; recommendation system; user study; speech emotion recognition; attention mechanism; recurrent neural network; long short-term memory; user experience; usability evaluation methods; domain usability; domain-specific languages; graphical user interfaces; virtual reality; art therapy; rehabilitation; neurorehabilitation; neuroplasticity; brain injury; ASR; speech-to-text; edge AI; Wav2Vec; transformers; PyTorch; emotion recognition; dimensional to categorical emotion representation mapping; activation; arousal and valence regression; X-vectors; SVM; n/a