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Sensors and artificial intelligence methods and algorithms for human - computer intelligent interaction: a systematic mapping study
Boštjan Šumak, Saša Brdnik, Maja Pušnik, 2022, izvirni znanstveni članek

Opis: To equip computers with human communication skills and to enable natural interaction between the computer and a human, intelligent solutions are required based on artificial intelligence (AI) methods, algorithms, and sensor technology. This study aimed at identifying and analyzing the state-of-the-art AI methods and algorithms and sensors technology in existing human–computer intelligent interaction (HCII) research to explore trends in HCII research, categorize existing evidence, and identify potential directions for future research. We conduct a systematic mapping study of the HCII body of research. Four hundred fifty-four studies published in various journals and conferences between 2010 and 2021 were identified and analyzed. Studies in the HCII and IUI fields have primarily been focused on intelligent recognition of emotion, gestures, and facial expressions using sensors technology, such as the camera, EEG, Kinect, wearable sensors, eye tracker, gyroscope, and others. Researchers most often apply deep-learning and instance-based AI methods and algorithms. The support sector machine (SVM) is the most widely used algorithm for various kinds of recognition, primarily an emotion, facial expression, and gesture. The convolutional neural network (CNN) is the often-used deep-learning algorithm for emotion recognition, facial recognition, and gesture recognition solutions.
Ključne besede: human–computer intelligent interaction, intelligent user interfaces, IUI, sensors, artificial intelligence
Objavljeno v DKUM: 31.03.2025; Ogledov: 0; Prenosov: 3
Celotno besedilo (8,70 MB)
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Influence of highly inflected word forms and acoustic background on the robustness of automatic speech recognition for human–computer interaction
Andrej Žgank, 2022, izvirni znanstveni članek

Opis: Automatic speech recognition is essential for establishing natural communication with a human–computer interface. Speech recognition accuracy strongly depends on the complexity of language. Highly inflected word forms are a type of unit present in some languages. The acoustic background presents an additional important degradation factor influencing speech recognition accuracy. While the acoustic background has been studied extensively, the highly inflected word forms and their combined influence still present a major research challenge. Thus, a novel type of analysis is proposed, where a dedicated speech database comprised solely of highly inflected word forms is constructed and used for tests. Dedicated test sets with various acoustic backgrounds were generated and evaluated with the Slovenian UMB BN speech recognition system. The baseline word accuracy of 93.88% and 98.53% was reduced to as low as 23.58% and 15.14% for the various acoustic backgrounds. The analysis shows that the word accuracy degradation depends on and changes with the acoustic background type and level. The highly inflected word forms’ test sets without background decreased word accuracy from 93.3% to only 63.3% in the worst case. The impact of highly inflected word forms on speech recognition accuracy was reduced with the increased levels of acoustic background and was, in these cases, similar to the non-highly inflected test sets. The results indicate that alternative methods in constructing speech databases, particularly for low-resourced Slovenian language, could be beneficial.
Ključne besede: human–computer interaction, automatic speech recognition, acoustic modeling, highly inflected word forms, acoustic background
Objavljeno v DKUM: 28.03.2025; Ogledov: 0; Prenosov: 2
Celotno besedilo (1,12 MB)
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An answer to "Who needs a stylus?" on handwriting recognition on mobile device
Andreas Holzinger, Gig Searle, Bernhard Peischl, Matjaž Debevc, 2012, objavljeni znanstveni prispevek na konferenci

Ključne besede: prepoznavanje pisave, mobilno računalništvo, komunikacija človek-stroj, handwriting recognition, pen-based input, mobile computer, human-computer interaction
Objavljeno v DKUM: 10.07.2015; Ogledov: 1509; Prenosov: 30
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Human-machine interfacing by decoding surface electromyogram
Dario Farina, Aleš Holobar, 2015, izvirni znanstveni članek

Ključne besede: decoding, electromyography, human computer interaction, neurons, accuracyuser interfaces
Objavljeno v DKUM: 25.05.2015; Ogledov: 1609; Prenosov: 0

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