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Intelligent Information Systems End of Chapter Solutions Reviews and Discussions 1. What are two successful applications of artificial intelligence in business? Two successful applications of artificial intelligence include decision-making support and robots. 2. What are three advantages of a robot over a human? Robots offer the following advantages over humans: • They do not fall in love with coworkers, get insulted, or call in sick. • They are consistent. • They can be used in environments that are hazardous to humans, such as working with radioactive materials. 3. What are two applications of case-based reasoning? In design and implementation of any case-based reasoning application, there are 4 Rs involved: retrieve, reuse, revise, and retain. They may mention any two Rs. 4. What are two applications that are not suitable for expert systems? The following applications are not suitable for expert systems: • There are well-structured numerical problems (such as payroll processing) involved. • The problems require human experts—for example, a combination of the five senses, such as taste and smell. Selecting a perfume is a problem better solved by human experts. 5. What are three characteristics of a sophisticated intelligent agent? Intelligent agent has the following characteristics: • Adaptability—able to learn from previous knowledge and go beyond information given previously • Autonomy—able to operate with minimum input • Collaborative behavior—able to work and cooperate with other agents to achieve a common objective have learned. 6. What is the role of the hidden layer in an artificial neural network? In an artificial neural network (ANN), the hidden layer plays a crucial role in the network's ability to learn complex patterns and relationships within the input data. Here's a framed answer for the question: The role of the hidden layer in an artificial neural network is paramount for its ability to perform complex tasks such as pattern recognition, classification, and regression. Unlike the input and output layers, which directly interface with the external environment, the hidden layer operates internally, processing and transforming the input data into a form that enables the network to learn and generalize from the provided examples. Specifically, the hidden layer serves as a feature extractor, where each neuron within this layer extracts relevant features or representations from the input data through weighted connections and activation functions. These features are often abstract and may not be directly interpretable by humans, but they capture essential characteristics of the input patterns that are crucial for making accurate predictions or classifications. Additionally, the hidden layer enables the neural network to model non-linear relationships between input and output variables by introducing non-linear transformations through activation functions. This allows the network to learn and represent complex mappings between inputs and outputs, making it capable of handling tasks that involve intricate decision boundaries or dependencies. Furthermore, the depth and width of the hidden layer significantly impact the network's capacity to learn and generalize. Deeper architectures with multiple hidden layers can capture hierarchical representations of data, enabling the network to learn more intricate patterns and relationships. Similarly, increasing the width of the hidden layer by adding more neurons enhances the network's expressive power, allowing it to capture a broader range of features from the input data. In summary, the hidden layer in an artificial neural network serves as a critical component for learning and representing complex patterns and relationships within the input data, enabling the network to perform various intelligent tasks such as classification, regression, and pattern recognition. 7. What are two examples of commercial NLP systems? Two examples of commercial NLP (Natural Language Processing) systems are: 1. IBM Watson: IBM Watson is a powerful NLP platform that provides a range of AI-powered services, including language understanding, sentiment analysis, and text classification. It is widely used in various industries for tasks such as customer support, healthcare analytics, and financial services. 2. Google Cloud Natural Language API: Google Cloud Natural Language API offers a suite of NLP tools that enable developers to extract insights from text data. It includes capabilities such as entity recognition, sentiment analysis, and syntax analysis. This API is utilized by businesses for tasks such as content classification, document analysis, and social media monitoring. 8. How do you define contextual computing? Contextual computing refers to the paradigm of designing and implementing computational systems that can understand, adapt to, and respond appropriately to the context in which they operate. This context encompasses various environmental factors such as user location, time, activity, device characteristics, and user preferences, among others. The goal of contextual computing is to create intelligent systems that can enhance user experiences, improve task efficiency, and provide personalized services by leveraging contextual information. At its core, contextual computing relies on the integration of sensors, data processing techniques, machine learning algorithms, and human-computer interaction principles to interpret and utilize contextual cues effectively. These cues enable the system to understand the user's current situation, intentions, and needs, allowing it to tailor its behavior, recommendations, and interactions accordingly. One key aspect of contextual computing is context-awareness, which involves continuously monitoring and analyzing contextual information to dynamically adapt system behavior and provide relevant services in real-time. For example, a context-aware mobile application may adjust its interface layout, content, or functionality based on factors such as the user's location, movement patterns, and current activity. Furthermore, contextual computing enables the development of intelligent assistants and proactive systems that anticipate user needs and preferences based on historical data and contextual cues. By leveraging contextual understanding, these systems can offer timely recommendations, automate routine tasks, and provide personalized assistance, thereby enhancing user productivity and satisfaction. In summary, contextual computing represents a fundamental shift in the way computational systems are designed and utilized, emphasizing the importance of understanding and responding to the contextual nuances of user interactions. By leveraging contextual information, these systems can deliver more relevant, personalized, and efficient experiences across various domains, ranging from mobile applications and smart environments to virtual assistants and wearable devices. Projects 1. After reading the information presented in this chapter and other sources, write a one-page paper that discusses the advantages and disadvantages of robotic surgery. When it comes to cost, which one is cheaper: human doctor or robot? The da Vinci surgical System is an example of a robot used in surgery. What are two positive and two negative aspects of this system? Robotic surgery has emerged as a revolutionary approach in modern healthcare, offering both advantages and disadvantages compared to traditional surgical methods. This paper examines the benefits and drawbacks of robotic surgery, particularly focusing on cost considerations and the da Vinci Surgical System as a prominent example. Advantages of Robotic Surgery: • Precision and Accuracy: Robotic systems like the da Vinci Surgical System offer unparalleled precision and accuracy, allowing surgeons to perform complex procedures with enhanced dexterity and control. The system translates the surgeon's hand movements into precise, scaled motions, reducing the risk of human error and improving surgical outcomes. • Minimally Invasive Techniques: Robotic surgery enables minimally invasive procedures, which typically result in smaller incisions, reduced blood loss, shorter hospital stays, and faster recovery times compared to traditional open surgery. Patients undergoing robotic surgery often experience less pain and scarring, leading to improved postoperative comfort and satisfaction. Disadvantages of Robotic Surgery: • Cost Considerations: One significant disadvantage of robotic surgery is its high cost. The initial investment in robotic systems, along with ongoing maintenance, training, and instrument expenses, can be substantial. Additionally, robotic procedures may require longer operating times, leading to increased anesthesia and operating room costs compared to traditional surgery. • Learning Curve and Training Requirements: Despite the benefits of robotic surgery, there is a steep learning curve associated with mastering the use of robotic systems. Surgeons and surgical teams require extensive training to become proficient in operating the robotic platform effectively. The complexity of robotic interfaces and the need for specialized skills may limit widespread adoption and accessibility, particularly in smaller healthcare facilities. Cost Comparison: Human Doctor vs. Robot When considering the cost of surgery, it is essential to weigh the expenses associated with human doctors versus robotic systems. While the upfront costs of robotic surgery may be higher due to equipment and maintenance expenses, there are long-term considerations to evaluate. Factors such as reduced hospital stays, fewer complications, and faster recovery times associated with robotic surgery can lead to overall cost savings in the long run. Additionally, as technology advances and robotic systems become more widespread, economies of scale may drive down the cost of robotic procedures, making them more cost-effective compared to traditional surgery. Positive Aspects of the da Vinci Surgical System: • Enhanced Visualization: The da Vinci Surgical System provides surgeons with high-definition, 3D visualization of the surgical site, allowing for improved depth perception and better identification of anatomical structures. This enhanced visualization facilitates precise tissue dissection and reduces the risk of inadvertent damage to surrounding tissues. • Ergonomic Design: The ergonomic design of the da Vinci system offers surgeons greater comfort and control during procedures, minimizing fatigue and optimizing performance. The system's intuitive interface and ergonomic console enable surgeons to operate with enhanced precision and efficiency, contributing to better surgical outcomes. Negative Aspects of the da Vinci Surgical System: • Cost Constraints: As mentioned earlier, the da Vinci Surgical System entails significant upfront costs for acquisition, maintenance, and instrument procurement. These expenses may present financial barriers for healthcare institutions, limiting access to robotic surgery for certain patient populations or healthcare facilities with budget constraints. • Limited Haptic Feedback: One drawback of robotic surgery systems like da Vinci is the limited haptic feedback experienced by surgeons. Unlike traditional surgery, where surgeons can directly feel and manipulate tissues, robotic systems provide only minimal tactile feedback. This lack of tactile sensation may pose challenges in delicate procedures requiring precise tissue manipulation and palpation. In conclusion, robotic surgery offers numerous advantages in terms of precision, minimally invasive techniques, and patient outcomes, but it also presents challenges such as high costs and training requirements. When considering the cost of surgery, it is essential to weigh the upfront expenses of robotic systems against potential long-term benefits such as reduced complications and faster recovery times. The da Vinci Surgical System exemplifies both the positive and negative aspects of robotic surgery, showcasing its potential to revolutionize healthcare while highlighting areas for improvement and further innovation. 2.Contextual computing has generated a lot of excitement in the computing community. After reading the information presented in this chapter and other sources, write a one-page paper that discusses the advantages and disadvantages of this platform. In addition to Google Now, what other software applications currently offer this capability? Contextual computing has emerged as a transformative paradigm in the computing community, offering a plethora of advantages while also presenting certain challenges. This paper examines the benefits and drawbacks of contextual computing and explores additional software applications beyond Google Now that offer this capability. Advantages of Contextual Computing: • Personalized User Experiences: Contextual computing enables software applications to understand and adapt to the user's context, preferences, and behavior. By leveraging contextual information such as location, time, and user activity, these applications can deliver personalized recommendations, content, and services tailored to individual users, enhancing user satisfaction and engagement. • Enhanced Task Efficiency: Contextual computing facilitates seamless integration and automation of tasks based on the user's context. Applications can anticipate user needs and proactively provide relevant information or assistance, streamlining workflow processes and improving overall task efficiency. This proactive approach saves users time and effort by reducing the need for manual input and decision-making. • Improved Decision Making: By analyzing contextual data in real-time, contextual computing systems empower users to make more informed decisions. Whether it's suggesting nearby restaurants based on location and user preferences or providing timely reminders based on the user's schedule, these applications help users make better choices by presenting relevant information within the appropriate context. Disadvantages of Contextual Computing: • Privacy and Data Security Concerns: Contextual computing relies heavily on collecting and analyzing user data to infer context and deliver personalized experiences. However, this raises concerns about privacy and data security, as sensitive information such as location, browsing history, and personal preferences may be vulnerable to exploitation or unauthorized access. Striking a balance between personalized experiences and user privacy remains a significant challenge for contextual computing systems. • Dependency on Data Accuracy and Availability: The effectiveness of contextual computing hinges on the accuracy and availability of contextual data. Inaccurate or incomplete data can lead to erroneous assumptions and suboptimal user experiences. Additionally, contextual computing systems may struggle in environments with limited connectivity or unreliable data sources, hindering their ability to provide timely and accurate contextual insights. Other Software Applications Offering Contextual Computing Capabilities: • Amazon Alexa: Amazon's virtual assistant, Alexa, employs contextual computing to understand user requests, preferences, and habits. By analyzing user interactions and integrating with various smart home devices, Alexa delivers personalized responses and automates tasks based on the user's context, such as controlling smart home devices or providing personalized recommendations. • Microsoft Cortana: Cortana, Microsoft's virtual assistant, utilizes contextual computing to assist users across different devices and platforms. By learning from user interactions and integrating with Microsoft services, Cortana offers proactive suggestions, reminders, and personalized recommendations tailored to the user's context and preferences. In conclusion, contextual computing offers numerous advantages in terms of personalized user experiences, task efficiency, and decision making. However, it also poses challenges related to privacy, data security, and data accuracy. Beyond Google Now, other software applications such as Amazon Alexa and Microsoft Cortana leverage contextual computing capabilities to deliver tailored experiences and enhance user productivity across various domains. As contextual computing continues to evolve, addressing these challenges while harnessing its potential for innovation remains crucial in shaping the future of computing. 3. Nina, from Nuance.com, is being marketed as an intelligent agent. After reading the information presented in this chapter and other sources, write a one-page paper that explains the applications of this software. What types of businesses will benefit the most from it? Nina, developed by Nuance.com, represents a significant advancement in the realm of intelligent agents, offering a wide range of applications across various industries. This paper delves into the practical uses of Nina and identifies the types of businesses poised to benefit the most from this innovative software solution. Applications of Nina: • Customer Service and Support: Nina serves as a virtual customer service representative, capable of understanding and responding to customer inquiries and requests in natural language. Businesses can deploy Nina on their websites, mobile apps, or interactive voice response (IVR) systems to provide instant assistance, answer frequently asked questions, and resolve customer issues efficiently. By automating routine inquiries and offering personalized support, Nina enhances the customer service experience and reduces the burden on human agents. • Appointment Scheduling and Booking: Nina's natural language processing capabilities enable seamless appointment scheduling and booking processes. Businesses in industries such as healthcare, hospitality, and professional services can integrate Nina into their scheduling systems to allow customers to book appointments, make reservations, or request services through conversational interfaces. Nina streamlines the booking process, minimizes scheduling conflicts, and enhances customer convenience, leading to improved operational efficiency and customer satisfaction. • Sales and Product Recommendations: Nina can act as a virtual sales assistant, guiding customers through product catalogs, recommending relevant offerings, and facilitating purchases. E-commerce businesses can leverage Nina to provide personalized product recommendations based on customer preferences, browsing history, and purchase behavior. By engaging customers in interactive conversations and offering tailored suggestions, Nina drives sales conversions, increases average order value, and fosters customer loyalty. • Financial Services and Banking: Nina's intelligent agent capabilities extend to the financial services sector, where it can assist customers with account inquiries, transaction history, and financial planning. Banks and financial institutions can deploy Nina on their digital channels to enable customers to check account balances, transfer funds, or receive personalized financial advice through natural language interactions. Nina enhances the accessibility of financial services, improves customer engagement, and strengthens brand loyalty in an increasingly competitive market. Types of Businesses Benefiting Most from Nina: • Large Enterprises with High Customer Interaction Volumes: Businesses with large customer bases and high volumes of customer inquiries stand to benefit significantly from Nina's ability to automate and streamline customer interactions. Industries such as telecommunications, retail, and healthcare, which experience frequent customer queries and support requests, can leverage Nina to scale their customer service operations efficiently and deliver consistent, high-quality support experiences. • Service-Oriented Businesses Requiring Appointment Management: Businesses that rely on appointment scheduling and booking processes, such as healthcare providers, beauty salons, and professional service firms, can leverage Nina to optimize their appointment management workflows. Nina's conversational interface simplifies the scheduling process for both customers and service providers, reducing administrative overhead and improving resource utilization. In conclusion, Nina by Nuance.com offers versatile applications across diverse industries, ranging from customer service and appointment scheduling to sales assistance and financial services. Businesses with extensive customer interactions and service-oriented operations stand to benefit the most from Nina's intelligent agent capabilities, as it enables them to automate routine tasks, enhance customer experiences, and drive business growth in today's digital economy. 4. Case-based reasoning systems have been used in a variety of disciplines. In the future, they may also be used in the medical field. After reading the information presented in this chapter and other sources, write a one-page paper that explains how case-based reasoning systems will be used in this area. How might that bring healthcare costs down? Case-based reasoning (CBR) systems offer a promising approach to revolutionize the medical field by leveraging past cases to inform current diagnoses and treatment decisions. This paper explores the potential applications of CBR systems in healthcare and elucidates how their adoption could contribute to cost reduction within the industry. Utilizing CBR Systems in Healthcare: • Diagnostic Support: CBR systems can assist healthcare providers in diagnosing complex medical conditions by analyzing similarities between current patient cases and archived cases with known diagnoses and treatment outcomes. By comparing symptoms, medical history, test results, and treatment responses, CBR systems help clinicians identify relevant precedents and make informed decisions about patient care. This approach enhances diagnostic accuracy, reduces diagnostic errors, and ensures consistency in decision-making across healthcare settings. • Treatment Planning and Personalization: CBR systems enable personalized treatment planning by recommending interventions based on the success of similar cases in the past. By considering factors such as patient demographics, comorbidities, genetic profiles, and treatment responses, these systems help clinicians tailor treatment regimens to individual patient needs, preferences, and characteristics. This personalized approach maximizes treatment effectiveness, minimizes adverse effects, and improves patient outcomes while optimizing resource utilization. • Medical Education and Training: CBR systems serve as valuable educational tools for medical students, residents, and practicing clinicians by providing access to a repository of diverse clinical cases and expert knowledge. These systems facilitate experiential learning through case-based simulations, virtual patient encounters, and decision-making exercises, enabling healthcare professionals to develop diagnostic and therapeutic skills in a risk-free environment. By promoting continuous learning and knowledge sharing, CBR systems contribute to the professional development of healthcare providers and enhance the quality of care delivery. Cost Reduction Potential: • Efficient Resource Allocation: By facilitating accurate diagnosis and personalized treatment planning, CBR systems help healthcare organizations optimize resource allocation and utilization. By minimizing unnecessary diagnostic tests, procedures, and treatments, CBR systems reduce healthcare waste and lower overall costs associated with redundant or ineffective interventions. Additionally, by identifying cost-effective treatment options and avoiding costly complications, CBR systems contribute to cost containment efforts and promote fiscal responsibility in healthcare delivery. • Reduced Medical Errors and Readmissions: CBR systems mitigate the risk of medical errors and adverse events by providing clinicians with evidence-based guidance and decision support. By standardizing diagnostic and treatment protocols, promoting adherence to best practices, and alerting providers to potential risks and contraindications, CBR systems improve patient safety and reduce the incidence of preventable complications. This proactive approach not only enhances patient outcomes but also minimizes the financial burden associated with avoidable hospital readmissions, extended hospital stays, and malpractice claims. In conclusion, the integration of case-based reasoning systems in healthcare holds immense potential to revolutionize clinical decision-making, improve patient outcomes, and mitigate healthcare costs. By harnessing the wealth of knowledge embedded in past clinical cases, CBR systems empower healthcare providers to make informed decisions, tailor treatments to individual patient needs, and optimize resource utilization, ultimately driving efficiency and affordability in healthcare delivery. 5. Intelligent agents are being used in a variety of applications. After reading the information presented in this chapter and other sources, write a one-page paper that discusses the applications of these agents in the e-commerce environment. Identify three such agents and their specific applications in e-commerce. Intelligent agents have become indispensable tools in the e-commerce environment, offering innovative solutions to enhance customer experiences, streamline operations, and drive business growth. This paper explores the diverse applications of intelligent agents in e-commerce and identifies three notable examples along with their specific applications. Applications of Intelligent Agents in E-commerce: 1. Personalized Recommendation Systems: Intelligent recommendation agents play a pivotal role in e-commerce by analyzing user preferences, browsing behavior, and purchase history to deliver personalized product recommendations. These agents leverage machine learning algorithms to understand individual customer preferences and tailor recommendations accordingly, thereby increasing the likelihood of successful purchases and improving customer satisfaction. For example, Amazon's recommendation engine utilizes collaborative filtering and predictive analytics to suggest products based on past purchases, viewed items, and similar users' behaviors, enhancing the overall shopping experience and driving sales. 2. Virtual Shopping Assistants: Virtual shopping assistants provide personalized assistance to online shoppers by answering questions, providing product information, and guiding them through the purchase process. These agents utilize natural language processing (NLP) and conversational interfaces to engage with customers in real-time, offering recommendations, addressing concerns, and facilitating transactions. One notable example is eBay's ShopBot, an AI-powered virtual assistant integrated into the eBay platform, which helps users find products, compare prices, and complete purchases through interactive chat interactions. By providing personalized assistance and guidance, virtual shopping assistants enhance customer engagement, reduce friction in the purchasing journey, and increase conversion rates. 3. Dynamic Pricing and Competitive Intelligence: Intelligent pricing agents enable e-commerce businesses to optimize pricing strategies based on market dynamics, competitor pricing, and customer demand. These agents leverage data analytics and predictive modeling to analyze market trends, identify pricing opportunities, and dynamically adjust prices in real-time to maximize profitability. For instance, airline and hotel booking platforms utilize intelligent pricing algorithms to adjust fares and room rates based on factors such as demand fluctuations, booking patterns, and competitor pricing strategies. By implementing dynamic pricing strategies, e-commerce businesses can stay competitive, maximize revenue, and adapt to changing market conditions efficiently. In conclusion, intelligent agents play a vital role in driving innovation and efficiency in the e-commerce environment, offering personalized recommendations, virtual assistance, and dynamic pricing capabilities. Through their applications, such as personalized recommendation systems, virtual shopping assistants, and dynamic pricing algorithms, intelligent agents empower e-commerce businesses to deliver superior customer experiences, increase sales, and maintain competitiveness in the digital marketplace. As technology continues to evolve, the role of intelligent agents in e-commerce is expected to expand further, offering new opportunities for businesses to innovate and differentiate themselves in the competitive landscape. 6. Nuance Communication’s Dragon Speech Recognition Software and AT&T’s Natural VoicesWizzard Speech are two of the popular commercial NLPs currently on the market. After reading the information presented in this chapter and other sources, write a two-page paper that explains key features of each NLP. What are some of the business applications of each software? What types of businesses will benefit the most from these types of software? Introduction: Nuance Communication's Dragon Speech Recognition Software and AT&T's Natural Voices Wizzard Speech are leading commercial natural language processing (NLP) solutions that offer advanced features and applications across various industries. This paper provides an in-depth analysis of the key features of each NLP software and explores their business applications, highlighting the types of businesses poised to benefit the most from their capabilities. Nuance Communication's Dragon Speech Recognition Software: Key Features: • Accurate Speech Recognition: Dragon Speech Recognition Software leverages advanced algorithms and machine learning techniques to accurately transcribe spoken words into text with high precision and speed. The software continuously adapts to user speech patterns and accents, ensuring reliable performance across diverse environments and languages. • Voice Command Capabilities: Dragon enables users to perform hands-free operations and control applications using voice commands. Users can dictate documents, compose emails, navigate websites, and execute commands within software applications, enhancing productivity and accessibility for individuals with disabilities or mobility impairments. • Customization and Integration: Dragon offers extensive customization options, allowing users to create personalized voice profiles, vocabularies, and commands tailored to their specific needs and preferences. The software seamlessly integrates with popular productivity tools, electronic health record (EHR) systems, customer relationship management (CRM) platforms, and other business applications, enabling seamless workflow integration and automation. Business Applications: • Healthcare Documentation: Dragon is widely used in the healthcare industry for clinical documentation, enabling physicians, nurses, and other healthcare professionals to dictate patient notes, medical records, and diagnostic reports directly into EHR systems. By streamlining documentation processes and reducing administrative burdens, Dragon improves efficiency, accuracy, and compliance in healthcare settings. • Legal Transcription and Dictation: Law firms and legal professionals leverage Dragon for transcription and dictation tasks, allowing lawyers to dictate case notes, legal documents, and correspondence with clients. The software accelerates document creation, facilitates collaboration among legal teams, and enhances workflow efficiency in legal practices. • Customer Service and Call Centers: Dragon enhances customer service operations by enabling call center agents to transcribe and analyze customer interactions in real-time. By automatically transcribing phone conversations, identifying customer sentiments, and extracting key insights, Dragon helps businesses improve service quality, resolve inquiries efficiently, and identify opportunities for process optimization. Businesses That Benefit Most: • Healthcare Providers and Clinics: Healthcare organizations benefit significantly from Dragon's ability to streamline clinical documentation, improve EHR usability, and enhance provider productivity. By reducing documentation time and enabling more accurate record-keeping, Dragon enhances patient care quality and regulatory compliance in healthcare settings. • Legal Firms and Practices: Legal professionals rely on Dragon to expedite document creation, transcription, and dictation tasks, enabling lawyers to focus on core legal activities and client representation. Law firms of all sizes benefit from Dragon's efficiency gains, cost savings, and improved client service delivery. • Call Centers and Customer Support Teams: Businesses with call center operations leverage Dragon to enhance customer service quality, optimize call handling processes, and extract valuable insights from customer interactions. Dragon's real-time transcription capabilities empower call center agents to provide personalized assistance, resolve issues promptly, and drive customer satisfaction and loyalty. AT&T's Natural Voices Wizzard Speech: Key Features: • Natural and Human-like Voice Synthesis: AT&T's Natural Voices Wizzard Speech employs advanced text-to-speech (TTS) synthesis techniques to generate natural-sounding speech output that closely resembles human speech patterns and intonation. The software offers a variety of voice styles, accents, and languages to suit diverse applications and audience preferences. • Multi-Platform Compatibility: Wizzard Speech is compatible with various operating systems, platforms, and devices, including desktop computers, mobile devices, IVR systems, and embedded applications. The software supports integration with web browsers, mobile apps, virtual assistants, and interactive voice response (IVR) systems, enabling seamless deployment across different environments. • Customization and Branding Options: Wizzard Speech provides customization capabilities for voice characteristics, pronunciation, and language settings, allowing users to create branded voice experiences tailored to their specific requirements. Businesses can customize voice prompts, audio messages, and interactive voice applications to align with their brand identity and enhance customer engagement. Business Applications: • Interactive Voice Response (IVR) Systems: Wizzard Speech powers IVR systems for businesses and organizations, enabling automated customer service interactions, information delivery, and transaction processing over the phone. By synthesizing natural-sounding voice prompts and responses, Wizzard Speech enhances IVR usability, reduces caller frustration, and improves self-service efficiency. • Accessibility Solutions: Wizzard Speech enhances accessibility for individuals with visual impairments or reading difficulties by converting text-based content into speech output. The software enables websites, mobile apps, e-books, and digital documents to offer audio versions or voice-enabled navigation features, making digital content more accessible and inclusive. • Interactive Media and Entertainment: Wizzard Speech facilitates the creation of interactive media experiences, such as virtual assistants, gaming applications, and interactive storytelling platforms. By incorporating natural-sounding voice synthesis, Wizzard Speech enhances user immersion, interactivity, and engagement in digital entertainment content. Businesses That Benefit Most: • Enterprises with IVR Systems: Businesses operating call centers, customer support hotlines, and automated phone systems leverage Wizzard Speech to enhance IVR usability, streamline call handling processes, and deliver personalized customer experiences. Wizzard Speech enables businesses to provide automated assistance, conduct surveys, and process transactions efficiently, reducing call wait times and improving customer satisfaction. • Digital Content Providers: Media companies, e-learning platforms, and publishers utilize Wizzard Speech to enhance the accessibility and engagement of digital content for diverse audiences. By offering audio versions of articles, books, and educational materials, Wizzard Speech enables content providers to reach wider audiences, improve content consumption experiences, and comply with accessibility regulations. • Entertainment and Gaming Industry: Game developers, virtual reality (VR) creators, and interactive media producers leverage Wizzard Speech to enhance user experiences in digital entertainment and gaming applications. By incorporating natural-sounding voice synthesis into characters, narrations, and interactive elements, Wizzard Speech enhances immersion, storytelling, and player engagement, driving user satisfaction and retention. Conclusion: Nuance Communication's Dragon Speech Recognition Software and AT&T's Natural Voices Wizzard Speech are powerful NLP solutions that offer distinct features and applications across various industries. Dragon excels in accurate speech recognition, voice command capabilities, and integration with business applications, making it well-suited for healthcare documentation, legal transcription, and customer service operations. On the other hand, Wizzard Speech specializes in natural voice synthesis, multi-platform compatibility, and customization options, making it ideal for IVR systems, accessibility solutions, and interactive media applications. Businesses across healthcare, legal, customer service, media, entertainment, and gaming sectors stand to benefit from the unique capabilities of these NLP solutions, as they enable improved productivity, customer engagement, and operational efficiency in the digital era. Are You Ready to Move On? 1. In an expert system environment, in forward chaining, a series of “if-then-else” condition pairs is performed. The “if” condition is evaluated first, then the corresponding “then-else” action is carried out. Answer: True 2. An artificial neural network uses if-then-else in order to solve a problem. Answer: False 3. Selection and crossover are two of the techniques used by a genetic algorithm. Answer: True 4. Which of the following is not among the components of an expert system? a. Knowledge base b. Credit rating facility c. Inference engine d. Knowledge acquisition facility Answer: b 5. Which of the following is not among the characteristics of a sophisticated intelligent agent? a. Adaptability b. Collectivity c. Autonomy d. Mobility Answer: b 6. Which of the following is not a category of NLP system? a. Computer code generator b. Interface to databases c. Machine translation d. Text scanning Answer: a Case Studies Case Study 13-1: AI-Based Software Helps Businesses Better Understand Customers 1. What problems were Scotts Miracle Gro facing? Scotts Miracle-Gro, a major provider of lawn, garden, and outdoor-living products and services, recently noticed that a large number of customers were canceling lawn-fertilizer service. 2. Which software was used to analyze data collected by Scotts? An AI-based software called Luminoso was used to analyze data collected by Scotts. 3. How does a software tool such as Luminoso analyze data? Luminoso performs its analyses by accessing a large database that stores common sense knowledge and relationships (such as “if you drop a ball, it will fall”) that help to understand how words and phrases relate to each other. 4. What are some strategic applications of software tool such as Luminoso? AI-based software is getting smarter at analyzing qualitative data, words, phrases, and understanding the relationship among these words. These programs are able to analyze data generated though focus groups, surveys, online forums, call centers, help desks, and social media, and are able to generate new insights. Such new insights could help businesses offer better customer service and products and services that are more appealing to their customers. Case Study 13-2: NLP: Making a Smartphone Smarter 1. How can NLP make a smartphone smarter? NLP adds a user friendly environment and enhances data entry and data input for mobile users. And the increased memory and speed of mobile devices (as well as the increased speed of mobile and wireless networks) make them good candidates for NLP. As a result, voice-activated functions, speech-to-text dictation, and voice-activated dialing are now available for most smartphones, and voice-driven apps are getting smarter. For example, instead of saying “Call 551-535-1922” to dial a phone number, users can now say “Dial Dad” or “Phone my father.” 2. What are some examples of voice-based software used by iPhone? Nuance’s Dragon Dictation, available as an iPhone app, allows users to dictate everything from memos and e-mails to Twitter updates; Dragon for E-mail offers similar capabilities for the BlackBerry. Also for the iPhone, Jibbigo translates words, phrases, and simple sentences. Voice-driven apps such as Google Voice Search, Bing Voice Search, and Microsoft Tellme are among the more popular smartphone applications. Apple’s Siri is a new entrant in the fast-growing voice-activated mobile-device market, having been added to the iPhone 4S and beyond. 3. What are some of the challenges that have to be overcome before achieving a full-featured voice-activated mobile device? One of the challenges with voice-activated mobile devices is to get the device to understand what one means, not just what one says. Other challenges include the use of foreign names, accents, and maintaining accuracy in noisy environments. Solution Manual for MIS Hossein Bidgoli 9781305632004, 9781337625999, 9781337625982, 9781337406925
