Cortana Research Articles

Transforming User Experience (UX) through Artificial Intelligence (AI) in Interactive Media Design

This paper discusses the application and advantages of artificial intelligence technology in digital media interactive product design. Firstly, the development background of artificial intelligence technology and its promoting effect on design innovation is introduced, and the application of new technologies, such as generative adversarial networks in art creation and design personalization, is definitely analyzed. It then explores in detail the ability of AI to break traditional constraints in interactive design, innovate design, and optimize user experience, especially in digital media. Finally, the case study of Microsoft Cortana shows the method of classifying and processing user queries by machine learning system and its experimental results. The research of this paper provides the theoretical basis and empirical support for the application of artificial intelligence technology in the future interactive design of digital media and has important academic and practical significance.

Comparative Study for Virtual Personal Assistants (VPA) and State-of-the-Art Speech Recognition Technology

Numerous types of virtual assistants have emerged as a result of the widespread use of smartphones, the expansion of their services, the tremendous advancements in automatic speech recognition and AI, and the growing reliance on virtual personal assistants (VPAs) for basic daily tasks like playing music, sending texts, making restaurant reservations, and getting weather updates. The popularity of virtual personal assistants is largely attributable to their convenient blend of user-friendliness and natural language interaction. This study comprehensively examines various virtual personal assistants powered by AI. It briefly overviews each, such as Microsoft Cortana, Samsung Bixby, Apple SIRI, Google Assistant, and Amazon Alexa. This study also includes a comprehensive overview of the state-of-the-art speech recognition used in virtual personal assistants. The findings show that each Virtual Personal Assistant has advantages, and a user may select any of them depending on his preferences and needs.

Transforming User Experience (UX) through Artificial Intelligence (AI) in interactive media design

This paper discusses the application and advantages of artificial intelligence technology in digital media interactive product design. Firstly, the development background of artificial intelligence technology and its promoting effect on design innovation is introduced, and the application of new technologies, such as generative adversarial networks in art creation and design personalization, is definitely analyzed. It then explores in detail the ability of AI to break traditional constraints in interactive design, innovate design, and optimize user experience, especially in digital media. Finally, the case study of Microsoft Cortana shows the method of classifying and processing user queries by machine learning system and its experimental results. The research of this paper provides the theoretical basis and empirical support for the application of artificial intelligence technology in the future interactive design of digital media and has important academic and practical significance. Keywords: Artificial Intelligence Technology, Digital Media Interaction Design, Generate Adversarial Network, User Experience.

Blind Vision Voice Assistant

Visual Impaired Voice Assistants are software applications that have been designed to provide assistance to visually impaired people by using voice commands and text-to-speech technology. These Assistants use advanced technologies such as speech recognition, natural language processing, and text-to-speech to communicate with the user and perform tasks. The report will explore the history, technology, benefits, and limitations of Visual Impaired Voice Assistants. The history of these Assistants can be traced back to the 1960s when researchers started exploring the use of computers to help visually impaired people. In the early 2000s, Voice Assistants such as Microsoft's Cortana and Apple's Siri were introduced, which provided greater functionality and could perform a wide range of tasks using natural language processing. The technology behind Visual Impaired Voice Assistants includes speech recognition, natural language processing, and text-to-speech. Speech recognition converts spoken words into text, while natural language processing allows the Assistant to understand the context and intent of the user's input. Textto-speech technology converts digital text into spoken words. These technologies allow visually impaired users to access digital information and perform tasks without the need for visual assistance. The report will also highlight the benefits and limitations of Visual Impaired Voice Assistants. The benefits of these Assistants include increased independence, greater accessibility to digital information, and the ability to perform tasks that would have been difficult or impossible without assistance. However, the limitations of these Assistants include difficulty understanding certain accents or dialects and struggling with background noise. Finally, the report will discuss the impact of Visual Impaired Voice Assistants on the lives of visually impaired people. These Assistants have revolutionized the way visually impaired people interact with technology and the world around them. They have provided greater independence, increased accessibility, and helped to break down barriers, promoting inclusivity

Towards the Development of a Virtual Assistant for University Professors

A virtual assistant is an artificial intelligence software designed to perform various tasks and assist users in their daily activities. This technology is integrated into devices like smartphones, providing users with convenient, hands-free access. Popular virtual assistants include Amazon Alexa, Apple's Siri, Google Assistant, and Microsoft's Cortana. Today, virtual assistants are very popular in other contexts, such as education, because virtual assistants can function as customer service 24 hours a day, seven days a week, thus, for example, avoiding professors and service staff having to answer repetitive and easy-to-answer questions. In this work, we present an extended summary of the development of a virtual assistant for university professors. We are using a user-centered design approach to develop such a tool, as we want to involve end users from the beginning of the process. We hope to bring together several participants to obtain more valuable contributions

Health Information From Web Search Engines and Virtual Assistants About Pre-Exposure Prophylaxis for HIV Prevention in Adolescents and Young Adults: Content Analysis.

Adolescents and young adults are disproportionately affected by HIV, suggesting that HIV prevention methods such as pre-exposure prophylaxis (PrEP) should focus on this group as a priority. As digital natives, youth likely turn to internet resources regarding health topics they may not feel comfortable discussing with their medical providers. To optimize informed decision-making by adolescents and young adults most impacted by HIV, the information from internet searches should be educational, accurate, and readable. The aims of this study were to compare the accuracy of web-based PrEP information found using web search engines and virtual assistants, and to assess the readability of the resulting information. Adolescent HIV prevention clinical experts developed a list of 23 prevention-related questions that were posed to search engines (Ask.com, Bing, Google, and Yahoo) and virtual assistants (Amazon Alexa, Microsoft Cortana, Google Assistant, and Apple Siri). The first three results from search engines and virtual assistant web references, as well as virtual assistant verbal responses, were recorded and coded using a six-tier scale to assess the quality of information produced. The results were also entered in a web-based tool determining readability using the Flesch-Kincaid Grade Level scale. Google web search engine and Google Assistant more frequently produced PrEP information of higher quality than the other search engines and virtual assistants with scores ranging from 3.4 to 3.7 and 2.8 to 3.3, respectively. Additionally, the resulting information generally was presented in language at a seventh and 10th grade reading level according to the Flesch-Kincaid Grade Level scale. Adolescents and young adults are large consumers of technology and may experience discomfort discussing their sexual health with providers. It is important that efforts are made to ensure the information they receive about HIV prevention methods, and PrEP in particular, is comprehensive, comprehensible, and widely available.

Research Paper on Desktop Assistant

Abstract: The main thing of Artificial intelligence (AI) is the consummation of natural dialogue between humans and machines. There are numerous IT companies have used the dialogue systems technology to establish various kinds of Virtual assistants grounded on their operations and areas for adding commerce between mortal and machine, similar as Microsoft’s Cortana, Apple’s Siri, Amazon Alexa, Google Assistant. Like Microsoft Cortana we've created our own virtual desktop assistant only for Government College Of Engineering Chandrapur (GCOEC) using python which is suitable to run on any windows operating systems. We use python as a programming language because it has a multitude of libraries which can be used to create Artificial Intelligence. Our version of desktop assistant is capable of recognizing voice and voice commands. Desktop Assistant are programs on digital device like PC that hear and respond to verbal commands. Example, a user can say, “Open GCOEC Website” and the assistant will answer with the sanctioned website of GCOEC. Desktop Assistants can change the way of life of the people in a different manner. Bias is starting to build up in the community as AI’s are getting smarter in their own way to interact with humans in an easy language. The Desktop Assistant is a program that can fete mortal voices and can respond via integrated voice system. This paper will define the working of Desktop assistant, their main problems and limitations. In this paper it's described that the system of creating a Desktop assistant without using pall services, which will allow the expansion of similar bias in the future

El modelo de lenguaje basado en inteligencia artificial sensible - ChatGPT: Análisis bibliométrico y posibles usos en la agricultura y pecuaria

ChatGPT adds to the list of artificial intelligence-based systems designed to perform specific tasks and answer questions by interacting with users (Apple's Siri, Amazon's Alexa, Google's Assistant and Bard, Microsoft's Cortana, IBM's Watson, Bixby from Samsung, among others). ChatGPT works using OpenAI's GPT (Generative Pretrained Transformer) language model and is capable of learning from users' preferences and behavior patterns to customize its response. ChatGPT has the potential to be applied in different fields, including education, journalism, scientific writing, communication, cell biology, and biotechnology, where there is already evidence. The aim of this work was to analyze the possible applications of ChatGPT in the agricultural and livestock industry. First, a scientometric analysis was performed with VosViewer and Bibliometrix (Bliblioshiny). 3 clusters were identified: (a) Main characteristics; (b) learning systems you use; and (c) applications. To the question: What are the main applications in which ChatGTP will revolutionize agriculture (or livestock) in the world? ChatGPT responded: (a) in the agricultural field: improvement of agricultural decision-making, optimization of agricultural production, detection and prevention of plant diseases, climate management, and supply chain management; and (b) in the livestock field: improvement of animal health and welfare, optimization of animal production, supply chain management, detection and prevention of zoonotic diseases, and climate management for animal production. ChatGPT does not scientifically support its answer, but from the analysis carried out, we find that there is enough scientific evidence to conclude, in this case, that its answers were correct. While ChatGPT does not necessarily scientifically substantiate its answers, users should. There is a lack of studies on the use of Artificial Intelligence and its relationship with ethics.

AI and Arduino –Based Smart Home Robot Assistant

The creation of genuine conversation between humans and machines is the primary objective of artificial intelligence (AI). To increase the connection between humans and machines, numerous IT firmshave developed various types of Virtual Personal Assistants (VPAs) based on their applications and use cases, including Microsoft's Cortana, Apple's Siri, Amazon Alexa, and Google Assistant. Using Python, we have developed our own virtual personal assistant that is only available for Windows and can be accessed on any Windows explorer version, including Windows 7, 8, and 10. Python is used as a programming language because it has several important libraries that are used to carry out tasks. Our virtual assistant can identify and respond to the user's voice utilizing python installation packages. Because of how simple it is, home automation has become considerably more popular and in demand in recent years. Recently, work in this area has taken place, and a few systems that either use voice assistants or applications to manage electrical appliances have been developed. To administer the smart home and its various apps, an embedded system is employed as a local server. The findings show a variety of activities that the robot can take to answer the user's questions. The activities performed can be voice responses, mechanical moves, and motions, software tasks, or simply text messages.

Quality evaluation of digital voice assistants for diabetes management

<abstract><sec> <title>Background</title> <p>Digital voice assistants (DVAs) are increasingly used to search for health information. However, the quality of information provided by DVAs is not consistent across health conditions. From our knowledge, there have been no studies that evaluated the quality of DVAs in response to diabetes-related queries. The objective of this study was to evaluate the quality of DVAs in relation to queries on diabetes management.</p> </sec><sec> <title>Materials and methods</title> <p>Seventy-four questions were posed to smartphone (Apple Siri, Google Assistant, Samsung Bixby) and non-smartphone DVAs (Amazon Alexa, Sulli the Diabetes Guru, Google Nest Mini, Microsoft Cortana), and their responses were compared to that of Internet Google Search. Questions were categorized under diagnosis, screening, management, treatment and complications of diabetes, and the impacts of COVID-19 on diabetes. The DVAs were evaluated on their technical ability, user-friendliness, reliability, comprehensiveness and accuracy of their responses. Data was analyzed using the Kruskal-Wallis and Wilcoxon rank-sum tests. Intraclass correlation coefficient was used to report inter-rater reliability.</p> </sec><sec> <title>Results</title> <p>Google Assistant (n = 69/74, 93.2%), Siri and Nest Mini (n = 64/74, 86.5% each) had the highest proportions of successful and relevant responses, in contrast to Cortana (n = 23/74, 31.1%) and Sulli (n = 10/74, 13.5%), which had the lowest successful and relevant responses. Median total scores of the smartphone DVAs (Bixby 75.3%, Google Assistant 73.3%, Siri 72.0%) were comparable to that of Google Search (70.0%, p = 0.034), while median total scores of non-smartphone DVAs (Nest Mini 56.9%, Alexa 52.9%, Cortana 52.5% and Sulli the Diabetes Guru 48.6%) were significantly lower (p < 0.001). Non-smartphone DVAs had much lower median comprehensiveness (16.7% versus 100.0%, p < 0.001) and reliability scores (30.8% versus 61.5%, p < 0.001) compared to Google Search.</p> </sec><sec> <title>Conclusions</title> <p>Google Assistant, Siri and Bixby were the best-performing DVAs for answering diabetes-related queries. However, the lack of successful and relevant responses by Bixby may frustrate users, especially if they have COVID-19 related queries. All DVAs scored highly for user-friendliness, but can be improved in terms of accuracy, comprehensiveness and reliability. DVA designers are encouraged to consider features related to accuracy, comprehensiveness, reliability and user-friendliness when developing their products, so as to enhance the quality of DVAs for medical purposes, such as diabetes management.</p> </sec></abstract>

S1360 Can Voice Assistances (VA) Help Guide Hepatitis B Vaccination and Liver Disease Screening for the General Population?

Introduction: Engaging in behaviors that promote individual and population wellness continues to be a public health challenge; this pressing societal need requires innovative solutions. As the market for voice assistants (Amazon Alexa, Google Assistant, and Apple Siri) grows and people increasingly use them to assist in their daily tasks, there is a pressing need to explore how voice assistant (VA) technology can improve health-related behavior. Hepatitis B virus (HBV) infection is a major global cause of morbidity and mortality. Hepatitis B vaccines are highly effective in preventing infection and subsequent disease transmission and are safe. We did this study to determine if VAs provide clinically appropriate advice regarding Hepatitis B Vaccination and Hepatitis B virus. Methods: Four voice assistants: Apple Siri, Amazon Alexa, Google Assistant, and Microsoft Cortana, were tested. Voice recordings were done for 5 commonly asked questions regarding Hepatitis B vaccination and Liver Disease. The authors decided if each of the four VAs provided clinically appropriate advice. Fisher exact testing was done to compare the results of each VA against each other. Results: We found that clinically appropriate advice was provided 100% by Apple Siri, 60% by Amazon Alexa, 80% by Google Assistant, and 40% of the time by Microsoft Cortana (Table). Conclusion: The VAs provided accurate advice about when to start Hepatitis B Vaccination, including the May 2021 USPSTF recommendation. However, none of the VAs instructed participants to speak to a healthcare provider, which we believe is vital to any medically related search results. Most of the VAs performed well in our study, but we believe there is a need for improvement, especially with technology becoming more ingrained in our everyday lives.Figure 1.: Assessment of the clinical appropriateness of voice assistance results regarding Hepatitis B and Liver Disease.

My Voice Assistant Using Python

Abstract: In the current situation of technology development within the field of augmented reading and voice assistant systems development, many researchers are writing in this regard for the development of new and effective technologies. The voice assistant are software package agents that may interpret human speech & responds via synthesized voices apple siri, microsoft cortana & google assistant are the foremost common voice assistant & embedded in smartphones .Today the technological advancement is increasing day by day. with the assistance of computer system in which we are able to do solely few task however currently artificial intelligence ,machine learning and few a lot of technologies have created computer system so advance that we are able to implement any type of task. In the present paper, The thought of speech technology extremely encompasses 2 technologies: Synthesizer and recognizer. A speech synthesizer takes as input and produces an audio stream as output. A speech recognizer on the opposite hand does opposite. It takes an audio stream as input and thus turns it into text transcription. The voice may be a signal of infinite information. for this reason, we have got created our own virtual personal assistant just for windows using python 3.6 that is ready to right to use on any windows explorer such as windows 7,8,10.we will use python as a programming language as a result of it have a major libraries which is use to implement command. Index Term: Artificial Intelligence, Desktop Assistant, Python, Text to Speech, Virtual Assistant, Voice Recognition.

AI Based Virtual Assistance on Raspberry PI

Artificial intelligence (AI) technologies are one of the new technologies with new complicated features that are emerging at a fast pace. Although these technologies seem to be extensively adopted, people do not intend to use them in some cases. Technology adoption has been studied for many years, and there are many general models in the literature describing it. However, having more customized models for emerging technologies upon their features seems necessary. In this study, we developed a conceptual model involving a new system quality construct, i.e., interaction quality, which we believe can better describe adoption of AI-based technologies. In order to check our model, we used a voice assistant system (VAS) technology as an example of this technology, and tested a theory-based model using a data set achieved from a field survey. Our results confirm that interaction quality significantly affects individual’s trust and leads to adoption of this technology. Voice assistants are software agents that can interpret human speech and respond via synthesized voices. Apple's Siri, Amazon's Alexa, Microsoft's Cortana, and Google's Assistant are the most popular voice assistants and are embedded in smartphones or dedicated home speakers. Users can ask their assistants questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal commands. This column will explore the basic workings and common features of today's voice assistants. It will also discuss some of the privacy and security issues inherent to voice assistants and some potential future uses for these devices. As voice assistants become more widely used, librarians will want to be familiar with their operation and perhaps consider them as a means to deliver library services and materials.

An intelligent travel technology assessment model for destination impacts of tourist adoption

As intelligent travel technology creates a business trend to support the travel and tourism industry, it is necessary to create a complete model to assess the users in terms of continuous user acceptance and destination impacts which are Competitiveness, Loyalty, and Sustainability with entire stakeholders (travellers, service providers, and destinations). The proposed conceptual model is formulated based on four studies: A Plenary Free Individual Traveler Life Cycle, IS Success, IS Continuance, and Destination Impacts of Travel and Tourism. The sample and data collections were done through the online questionnaire and survey via social media platforms such as Facebook and Line with individuals who have used intelligent personal assistants such as Google Assistant, Apple Siri, Microsoft Cortana, Amazon Alexa, and Samsung Bixby for travel and tourism. 400 respondents were analyzed with descriptive statistics and inferential statistics using the measurement model and the structural model by PASW Statistics and SmartPLS.

Voice Assistants and Cancer Screening: A Comparison of Alexa, Siri, Google Assistant, and Cortana.

Despite increasing interest in how voice assistants like Siri or Alexa might improve health care delivery and information dissemination, there is limited research assessing the quality of health information provided by these technologies. Voice assistants present both opportunities and risks when facilitating searches for or answering health-related questions, especially now as fewer patients are seeing their physicians for preventive care due to the ongoing pandemic. In our study, we compared the 4 most widely used voice assistants (Amazon Alexa, Apple Siri, Google Assistant, and Microsoft Cortana) and their ability to understand and respond accurately to questions about cancer screening. We show that there are clear differences among the 4 voice assistants and that there is room for improvement across all assistants, particularly in their ability to provide accurate information verbally. In order to ensure that voice assistants provide accurate information about cancer screening and support, rather than undermine efforts to improve preventive care delivery and population health, we suggest that technology providers prioritize partnership with health professionals and organizations.

Meta-evaluation of Conversational Search Evaluation Metrics

Conversational search systems, such as Google assistant and Microsoft Cortana, enable users to interact with search systems in multiple rounds through natural language dialogues. Evaluating such systems is very challenging, given that any natural language responses could be generated, and users commonly interact for multiple semantically coherent rounds to accomplish a search task. Although prior studies proposed many evaluation metrics, the extent of how those measures effectively capture user preference remain to be investigated. In this article, we systematically meta-evaluate a variety of conversational search metrics. We specifically study three perspectives on those metrics: (1) reliability : the ability to detect “actual” performance differences as opposed to those observed by chance; (2) fidelity : the ability to agree with ultimate user preference; and (3) intuitiveness : the ability to capture any property deemed important: adequacy, informativeness, and fluency in the context of conversational search. By conducting experiments on two test collections, we find that the performance of different metrics vary significantly across different scenarios, whereas consistent with prior studies, existing metrics only achieve weak correlation with ultimate user preference and satisfaction. METEOR is, comparatively speaking, the best existing single-turn metric considering all three perspectives. We also demonstrate that adapted session-based evaluation metrics can be used to measure multi-turn conversational search, achieving moderate concordance with user satisfaction. To our knowledge, our work establishes the most comprehensive meta-evaluation for conversational search to date.

Natural Language Processing (NLP) and Its Impact across Industries – Unlocking the True Potential of Digital Healthcare (A Case Study Approach)

During the advent of the 21st century, technical breakthroughs and developments took place. Natural Language Processing or NLP is one of their promising disciplines that has been increasingly dynamic via groundbreaking findings on most computer networks. Because of the digital revolution the amounts of data generated by M2M communication across devices and platforms such as Amazon Alexa, Apple Siri, Microsoft Cortana, etc. were significantly increased. This causes a great deal of unstructured data to be processed that does not fit in with standard computational models. In addition, the increasing problems of language complexity, data variability and voice ambiguity make implementing models increasingly harder. The current study provides an overview of the potential and breadth of the NLP market and its acceptance in industry-wide, in particular after Covid-19. It also gives a macroscopic picture of progress in natural language processing research, development and implementation.

NATURAL LANGUAGE PROCESSING AND ITS EFFECTS ON SOCIETY AS A WHOLE: A SURVEY

Over the past 25 years, computational linguistics has grown to become both an interesting area of scientific research and upcoming technology that is increasingly being put into consumer products (for example, applications such as Apple’s Siri, Microsoft Cortana or Skype). There are main four key factors that are the driving force behind these developments: (i) an immense increase in computing power, (ii) the availability of huge amounts of linguistic data, (iii) the development of highly effective machine learning (ML) methods, and (iv)a more enriched understanding of the structure of human language and its application in social contexts.[2] Natural language processing (NLP) is the branch of Artificial Intelligence (AI) that deals with communication: How can a computer be programmed to understand, process, and generate language just like a human being? With the increasing use of the Web and other text application areas, there has been an increasing demand in both text mining and natural language processing (NLP). The main goal of Natural Language Processing (NLP) is to implement within computers the skill set required to understand a normal human language or natural language. It is related to the field of HCI ie. Human-Computer Interaction. One of the motivations of NLP is for the society whose access to web information is blocked simply by their inability to use the keyboard and OS. Natural language comes under the purview of AI with the goal of understanding and recreating meaningful expressions in human language. AI is the ability of a machine to imitate intelligent human behavior. This paper presents a survey on Natural language processing (NLP) and its effects on society as a whole. Here I talk about sentiment analysis which has a long-term effect on society. I also talk about social media mining which results in a huge amount of structured social information which is extremely important in the predictive analytics industry also. Then I discuss the future scope of NLP in the society.

Considerations on creating conversational agents for multiple environments and users

AbstractAdvances in artificial intelligence algorithms and expansion of straightforward cloud‐based platforms have enabled the adoption of conversational assistants by both, medium and large companies, to facilitate interaction between clients and employees. The interactions are possible through the use of ubiquitous devices (e.g., Amazon Echo, Apple HomePod, Google Nest), virtual assistants (e.g., Apple Siri, Google Assistant, Samsung Bixby, or Microsoft Cortana), chat windows on the corporate website, or social network applications (e.g. Facebook Messenger, Telegram, Slack, WeChat).Creating a useful, personalized conversational agent that is also robust and popular is nonetheless challenging work. It requires picking the right algorithm, framework, and/or communication channel, but perhaps more importantly, consideration of the specific task, user needs, environment, available training data, budget, and a thoughtful design.In this paper, we will consider the elements necessary to create a conversational agent for different types of users, environments, and tasks. The elements will account for the limited amount of data available for specific tasks within a company and for non‐English languages. We are confident that we can provide a useful resource for the new practitioner developing an agent. We can point out novice problems/traps to avoid, create consciousness that the development of the technology is achievable despite comprehensive and significant challenges, and raise awareness about different ethical issues that may be associated with this technology. We have compiled our experience with deploying conversational systems for daily use in multicultural, multilingual, and intergenerational settings. Additionally, we will give insight on how to scale the proposed solutions.

Speak2Code: A Multi-Utility Program based on Speech Recognition that Allows you to Code Through Speech Commands

Voice recognition has gained prominence and extensive use with the rise of Artificial Intelligence and that of the intelligent assistants such as Amazon's Alexa, Apple’s Siri and Microsoft's Cortana. Voice recognition systems enable Coders to interact with IDEs, Coding platforms, and tools related to Programming platforms simply by speaking to it. It is also extremely useful for hands free requests, reminders and other simple tasks. In this paper, the researcher has developed a program that simply elevates the use of speech commands to Code efficiently in the Integrated Development Environment and also to handle other related computer activities through the use of a Chat-Bot interface. The researcher has used Microsoft’s Speech Engine for Speech Recognition and Synthesis. This Research can prove immensely beneficial for ‘Visually Impaired Developers’ in the field of Computer Programming by helping them to code and accomplish huge coding possibilities, and challenges before them. This research would prove beneficial with a viewpoint of the concept also called as ‘Distant-Coding’ or ‘Remote-Coding’ in which the programmer can code from a remote place without been present in actual at the Company.