Developing a Graphical User Interface for an Artificial Intelligence-Based Voice Assistant

2021 ◽  
Vol 11 (3) ◽  
pp. 49-67
Author(s):  
Subhash S. ◽  
Siddesh S. ◽  
Prajwal N. Srivatsa ◽  
Ullas A. ◽  
Santhosh B.
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
Graphical User Interface ◽  
Human Life ◽  
Human Machine Interaction ◽  
Audio File ◽  
Voice User ◽  
Text Response ◽  
Intelligent Personal Assistant ◽  
The Voice

Artificial intelligence machineries have been extensively active in human life in recent times. Self-governing devices are enhancing their way of interacting with both human and devices. Contemporary vision in this topic can pave the way for a new process of human-machine interaction in which users will get to know how people can understand human language, adapting and communicating through it. One such tool is voice assistant, which can be incorporated into many other brilliant devices. In this article, the voice assistant will receive the audio from the microphone and then convert that into text, later with the help of ‘pyttsx3', and then the text response will be converted into an audio file; then the audio file will be played. The audio is processed using the voice user interface (VUI). This article develops a functional intelligent personal assistant (IPA) and integrates it with a graphical user interface that can perform mental tasks such as ON/OFF of smart applications based on the user commands.

scholarly journals Sign Translation Via Natural Language Processing

2021 ◽  
pp. 1-7
Author(s):  
Shadman A. Khan ◽  
Zulfikar Ali Ansari ◽  
Riya Singh ◽  
Mohit Singh Rawat ◽  
Fiza Zafar Khan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
Sign Language ◽  
Language Processing ◽  
New Technologies ◽  
End User ◽  
User Input ◽  
Sign Recognition ◽  
Voice User ◽  
The Voice

Artificial Intelligence (AI) technologies are new technologies with new complicated features emerging quickly. Technology adoption has been beneficial for many general models. The models help in train the voice user-interface assistance (Alexa, Cortona, Siri). Voice assistants are easy to use, and thus millions of devices incorporate them in households nowadays. The primary purpose of the sign language translator prototype is to reduce interaction barriers between deaf and mute. To overcome this problem, we have proposed a prototype. It is named sign language translator with Sign Recognition Intelligence which takes the user input in sign language and processes it, and returns the output in voice out load to the end-user.

scholarly journals Introducing a Virtual Assistant to the Lab: A Voice User Interface for the Intuitive Control of Laboratory Instruments

2018 ◽  
Vol 23 (5) ◽  
pp. 476-482 ◽  
Author(s):  
Jonas Austerjost ◽  
Marc Porr ◽  
Noah Riedel ◽  
Dominik Geier ◽  
Thomas Becker ◽  
...  
Keyword(s):  
User Interface ◽  
Low Vision ◽  
Chemical Substance ◽  
Smart Devices ◽  
Human Machine Interaction ◽  
General Applicability ◽  
New Era ◽  
Specific Device ◽  
Voice User ◽  
Voice User Interface

The introduction of smart virtual assistants (VAs) and corresponding smart devices brought a new degree of freedom to our everyday lives. Voice-controlled and Internet-connected devices allow intuitive device controlling and monitoring from all around the globe and define a new era of human–machine interaction. Although VAs are especially successful in home automation, they also show great potential as artificial intelligence-driven laboratory assistants. Possible applications include stepwise reading of standard operating procedures (SOPs) and recipes, recitation of chemical substance or reaction parameters to a control, and readout of laboratory devices and sensors. In this study, we present a retrofitting approach to make standard laboratory instruments part of the Internet of Things (IoT). We established a voice user interface (VUI) for controlling those devices and reading out specific device data. A benchmark of the established infrastructure showed a high mean accuracy (95% ± 3.62) of speech command recognition and reveals high potential for future applications of a VUI within the laboratory. Our approach shows the general applicability of commercially available VAs as laboratory assistants and might be of special interest to researchers with physical impairments or low vision. The developed solution enables a hands-free device control, which is a crucial advantage within the daily laboratory routine.

scholarly journals Application of Artificial Intelligence in User Interfaces Design for Cyber Security Threat Modeling

2021 ◽  
Author(s):  
Jide Ebenezer Taiwo Akinsola ◽  
Samuel Akinseinde ◽  
Olamide Kalesanwo ◽  
Moruf Adeagbo ◽  
Kayode Oladapo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
User Interfaces ◽  
Cyber Security ◽  
Security Threat ◽  
Human Machine Interaction ◽  
Daily Lives ◽  
Threat Modeling ◽  
Ui Design ◽  
Intelligent User Interface

In recent years, Cyber Security threat modeling has been discovered to have the capacity of combatting and mitigating against online threats. In order to minimize the associated risk, these threats need to be modelled with appropriate Intelligent User Interface (IUI) design and consequently the development and evaluation of threat metrics. Artificial Intelligence (AI) has revolutionized every facet of our daily lives and building a responsive Cyber Security Threat Model requires an IUI. The current threat models lack IUI, hence they cannot deliver convenience and efficiency. However, as the User Interface (UI) functionalities and User Experience (UX) continue to increase and deliver more astonishing possibilities, the present threat models lack the predictability capacity thus Machine Learning paradigms must be incorporated. Meanwhile, this deficiency can only be handled through AI-enabled UI that utilizes baseline principles in the design of interfaces for effective Human-Machine Interaction (HMI) with lasting UX. IUI helps developers or designers enhance flexibility, usability, and the relevance of the interaction to improving communication between computer and human. Baseline principles must be applied for developing threat models that will ensure fascinating UI-UX. Application of AI in UI design for Cyber Security Threat Modeling brings about reduction in critical design time and ensures the development of better threat modeling applications and solutions.

scholarly journals Prototyping neural networks to evaluate the risk of adverse cardiovascular outcomes in the population

2021 ◽  
Vol 6 (4) ◽  
pp. 67-81
Author(s):  
L. A. Bogdanov ◽  
E. A. Komossky ◽  
V. V. Voronkova ◽  
D. E. Tolstosheev ◽  
G. V. Martsenyuk ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Risk Factors ◽  
Neural Networks ◽  
User Interface ◽  
Arterial Hypertension ◽  
Graphical User Interface ◽  
Cross Validation ◽  
Cardiovascular Outcomes ◽  
Artery Disease

Aim. To develop a neural network basis for the design of artificial intelligence software to predict adverse cardiovascular outcomes in the population.Materials and Methods. Neural networks were designed using the database of 1,525 participants of PURE (Prospective Urban Rural Epidemiology Study), an international, multi-center, prospective study investigating disease risk factors in the urban and rural areas. As this study is still ongoing, we analysed only baseline data, therefore switching prognosis and diagnosis task. Because of its leading prevalence among other cardiovascular diseases, arterial hypertension was selected as an adverse outcome. Neural networks were designed employing STATISTICA Automated Neural Networks (SANN) software, manually selected, cross-validated, and transferred to the original graphical user interface software.Results. Input risk factors were gender, age, place of residence, concomitant diseases (i.e., coronary artery disease, chronic heart failure, diabetes mellitus, chronic obstructive pulmonary disease, and asthma), active or passive smoking, regular use of medications, family history of arterial hypertension, coronary artery disease or stroke, heart rate, body mass index, fasting blood glucose and cholesterol, high- and low-density lipoprotein cholesterol, and serum creatinine levels. Our neural networks showed a moderate efficacy in the virtual diagnostics of arterial hypertension (84.5%, or 1,289 successfully predicted outcomes out of 1,525, area under the ROC curve = 0.88), with almost equal sensitivity (83.6%) and specificity (85.3%), and were successfully integrated into graphical user interface that is necessary for the development of the commercial prognostication software. Cross-validation of this neural network on bootstrapped samples of virtual patients demonstrated sensitivity of 82.7 – 84.7%, specificity of 84.5 – 87.3%, and area under the ROC curve of 0.88 – 0.89.Conclusion. The artificial intelligence prognostication software to predict adverse cardiovascular outcomes in the population can be developed by a combination of automated neural network generation and analysis followed by manual selection, cross-validation, and integration into graphical user interface.

Evaluating Voice User Interfaces in Ubiquitous Applications

2010 ◽  
pp. 44-58
Author(s):  
Valéria Farinazzo Martins Salvador ◽  
João Soares de Oliveira Neto ◽  
Marcelo de Paiva Guimarães
Keyword(s):  
User Interface ◽  
User Interfaces ◽  
Current Trend ◽  
Evaluation Process ◽  
Quality Service ◽  
Voice User ◽  
The Voice ◽  
Natural Way ◽  
Voice User Interface

In the current trend of applications going more and more ubiquitous, it is necessary to determine some characteristics, requirements and properties that must be assured in order that the application provides quality service to its users. This chapter describes a study on the evaluation of Voice User Interface (VUI) in Ubiquitous Applications and discusses some of issues which may impact the evaluation process when using the voice as a natural way of interacting with computers. The authors present a set of guidelines and usability principles that should be considered when developing VUIs for Ubiquitous Applications. Finally, they present the results of a case study which was performed in order to test and exemplify the concepts presented here.

Extracting usability dimensions of the voice user interface - Focusing on AI assistants-

2020 ◽  
Vol 15 (1) ◽  
pp. 53-64
Author(s):  
Minjung Kim ◽  
Jieun Han ◽  
Hyo-Jin Kang ◽  
Gyu Hyun Kwon
Keyword(s):  
User Interface ◽  
Voice User ◽  
The Voice ◽  
Voice User Interface
Sign in / Sign up

Export Citation Format

Share Document