Smart Speakers Research Articles

Prevention of False Data Injection in Dataset using ML and DL

IoT is an interconnected and allotted network of embedded systems communicating through wired and wireless communication technology. It is defined as network of physical objects or things empowered with limited computation storage and conversation capabilities as well as embedded with electronics (sensors and actuators). Nowadays there are literally masses of hundreds of Internet of things (IoT) gadgets easily available to the customers. those consist of security cameras, smart home and smart speaker systems, smart toys and infant monitors, drones, domestic appliances, routers and internet gateways, and basically some other hardware products which can transmit information and be controlled over the net. FDIA is an attack this will result in a catastrophic outcomes. False information injection attack can be executed in each dynamic and static datasets, as a present device we easily discover and prevent in a static environment. in which with the present machine even the dynamic records is made static after which detects FDIA’s. FDIA in a static environment is the existing machine, in which we seek to have few solutions for the FDIA in a dynamic environment or for time collection information. So, to enhance protection in dynamic environment is our proposed challenge towards FDIA and we create a brand-new version known as “PdD” model – Predictive Dynamic version. Proposed framework performs crucial role in live streaming records in terms of heterogeneous environment (dynamic nature). So, we use GRU set of rules because it offers better RMSE value than different AI algorithms. This detects every time there may be a few FDI attack.

Better Data from AI Users: A Field Experiment on the Impacts of Robot Self-Disclosure on the Utterance of Child Users in Home Environment

Data are one of the important factors in artificial intelligence (AI). Moreover, in order for AI to understand the user and go beyond the role of a simple machine, the data contained in the user's self-disclosure is required. In this study, two types of robot self-disclosures (disclosing robot utterance, involving user utterance) are proposed to elicit higher self-disclosure from AI users. Additionally, this study examines the moderating effects of multi-robot conditions. In order to investigate these effects empirically and increase the implications of research, a field experiment with prototypes was conducted in the context of using smart speaker of children. The results indicate that both types of robot self-disclosures were effective in eliciting the self-disclosure of children. The interaction effect between disclosing robot and involving user was found to take a different direction depending on the sub-dimension of the user's self-disclosure. Multi-robot conditions partially moderate the effects of the two types of robot self-disclosures.

3D printed acoustic metamaterial filters for the mitigation of inaudible ultrasound attacks on smart speakers

Acoustic metamaterials have shown great potential in manipulating acoustic waves with a small footprint and versatile functionality. While their usefulness has been demonstrated in many fields including noise reduction and biomedical ultrasound, not many studies have been done in the field of audible acoustics and speakers. In this work, we show that an acoustic metamaterial-based filter can enhance the security of smart speakers, which are susceptible to inaudible ultrasound attacks due to the shadow effect of the microphones. The filter contains several resonant unit cells which collectively modulate the received signals in the ultrasound spectrum and, thus, mitigate inaudible attacks on smart speakers. On the other hand, normal audible signals are not affected and, therefore, regular functionality is not disturbed. The filtering effect is verified numerically using finite element analysis. Measurements are performed to validate the concept, where it is shown that inaudible ultrasound attacks are effectively blocked when the 3D-printed metamaterial filters are installed. This demonstration shows a possible way to apply acoustic metamaterials in consumer electronics such as smart speakers.

Nondestructive Data Acquisition Methodology for IoT Devices: A Case Study on Amazon Echo Dot Version 2

The smart speaker is becoming a common part of the modern household, which usually includes an AI-powered Intelligent Voice Assistant to communicate with its users. Amazon Echo Dot is a popular smart speaker that extends the above-stated functionality by acting as a communication hub for other Internet of Things (IoT) and mobile devices within its local network. The nature and volume of data that an Echo Dot handles make it a potential source of evidence, if one is seized for a digital forensics investigation. Researchers and practitioners have explored various techniques to extract data from these IoT devices. However, traditional methods make changes to the physical device and/or its data, which is undesirable from a digital forensics perspective. The current work focuses on developing a nondestructive methodology for extracting data from IoT devices, with Amazon Echo Dot version 2 as an example, which use embedded Multimedia Card (eMMC)/embedded Multichip Package (eMCP) chips as their primary storage. We identify all in-system programming (ISP) pins using the computed tomography (CT) Scan imagery of the main printed circuit board (PCB) of the device. We created a 3-D fixture that accommodates pogo pin connectors to create contact with the already identified ISP taps on the main PCB. The 3-D Test Probe Jig can extract data from an IoT device’s memory chip using an eMMC reader. The proposed nondestructive solution is reproducible, portable, and affordable.

Preface

The 6th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE 2022) was successfully held on October 28th-30th, 2022 in Xi’an China (virtual conference). ICEMCE 2022 created an ideal platform for experts, scholars and researchers engaged in Electrical, Mechanical and Computer Engineering to share views and experiences, promoting the application and development of theories and technologies and establishing business or research contacts for all the participants.In the conference, we were greatly honored to have Prof. Songgang Qiu from West Virginia University, USA a to serve as our Conference Chair. The conference covered keynote speeches, oral presentations and online Q&A discussion, attracting more than 160 delegates from all over the world. Firstly, the keynote speakers were each allocated 30-45 minutes to address their speeches. Then in the oral presentations, the excellent papers we had selected were presented by their authors one by one.Four sophisticated professors were invited to hold keynote speeches during the conference. Among them, Prof. Yang Xiao from Southwest Petroleum University, China performed a keynote speech on the title: Development of Key Technologies of Virtual Reality and Augmented Reality and Their Application. Focusing on the development trend of virtual reality and augmented reality technology, this study summarized the technical characteristics, the development status of key technologies, and the wide application of virtual reality and augmented reality, aiming at laying a more solid foundation for the continuous development and application of virtual reality augmented reality technology. Moreover, Prof. Yanjiao Chen from Zhejiang University, China made a report on Blackbox Enrollment-Phase Attacks on Smart Speaker Recognition Systems. In this presentation, we explored a new attack surface of SRSs by presenting an enrollment-phase attack paradigm, designed carefully continuous adversarial perturbations into innocent-sounding ambient sound, and optimized over adversarial segments with content desensitization and physical realization, reveals the vulnerability of SRSs during the enrollment phase, which may spur future research in improving the security of SRSs. Their dramatic speeches had triggered heated discussion. And every participant praised this conference for disseminating insightful knowledge.We are glad to share with you that we’ve selected a bunch of high-quality papers from the submissions and compiled them into the proceedings after rigorously reviewing them. These papers feature but are not limited to the following topics: Computer Simulation, Smart Grid, Electric Energy Processing, Mechanical Dynamics, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.We would like to acknowledge all of those who supported ICEMCE 2022 and made it a great success. Particularly, we would like to thank the Journal of Physics: Conference Series, for the efforts of all its colleagues in publishing this paper volume. We truly believe that all the attendees have had fruitful discussions and gained valuable knowledge, and will enjoy the opportunity for future collaborations.The Committee of ICEMCE 2022List of Committee member is available in this Pdf.

Voice Assistant Integrated with Chat GPT

AI has become deeply ingrained in the everyday life. The matter in question does not only touch upon the mobile phones that almost everyone carries within easy reach. Today, voice assistants and smart speakers are mainly used to turn on music, turn off the lights or forecast the weather. AI chatbots are getting smarter. The use of new technologies and the general development of neural networks makes it possible to chat or answer questions, write a script, a scientific work, or program code. One of the key differences from previous GPTs is that the new version is trained to continue the text and answer questions. The answers that the bot gives surprise users around the world. Yes, there are still questions about these answers and their validity, and everyone is sure that technology needs to be improved. For a technology to become revolutionary, it must find a better, new, breakthrough application. Although no, such an application has already been invented. Farcana decided to combine the functionality of the GPT chatbot and a voice assistant. By offering players a new approach to familiarizing themselves with game mechanics and general account management, Farcana promotes its advantages over others and rapidly contributes to AI's overall development in the digital society.

“Back to the living room era”: Smart speaker usage and family democracy from the family dynamic perspective

Based on joint media engagement (JME) and parental mediation theory (PMT), this study conducted a textual and thematic analysis of 360 user-generated content videos to explore, in the family scenario, smart speaker use behavior between Chinese children and parents. The findings reveal the following: (a) smart speakers create a new JME model and new co-use scenarios; (b) the mediation strategy used by parents differs from the mediation strategies in traditional PMT; (c) smart speakers are social actors and play a mediating role in the construction of family relationships; and (d) smart speaker use behavior between parents and children is characterized by a return to the living room era, which creates a new family dynamic and a reshaping of family politics.

Can healthcare apps and smart speakers improve the health behavior and depression of older adults? A quasi-experimental study.

This study identified the effects of applying information and communication technologies (ICT) to the health management of older adults aged 65 or older. Older adults registered at public health centers were provided with the health management app "Health Today" and a smart speaker for 6 months to perform assigned healthcare missions. The program was conducted for 6 months by dividing participants into two groups: one that received both the health management app and the smart speaker, and another that used only the health management app. Depression, self-efficacy, number of days of moderate-intensity exercise, relative grip strength, balance tests, and five-times-sit-to-stand tests were measured during the pre- and post-evaluation. Both groups showed a positive health status and behavioral changes at post-evaluation. However, no reduced depression was observed due to communication and music listening functions in the group that was additionally provided smart speakers. ICT use in healthcare can be beneficial for older adults. However, whether these devices meet the purpose of the national health project must be determined, and an effect evaluation must be undertaken prior to providing these ICT devices for the health management of older adults in the public domain.

The Unit and Size of Information Supporting Auditory Feedback for Voice User Interface

The purpose of this study was to explore the unit of information and the size of the unit for designing a voice user interface. Through two experiments, this study investigated what form the information (the unit of information) should take and what size of that (the size of unit) should be when people were provided information by voice interfaces. Participants were presented with a task to recall (OX quiz) by listening to and remembering information (based on an encyclopedia) provided by smart speakers. In Experiment 1, it was revealed that participants stored information in their memory span on a sentence-by-sentences basis to determine how much information they could remember. In Experiment 2, sentence-based information was presented in various sizes, and participants evaluated 17 information units consisting of up to nine words as their memory limit. This information unit-based voice interface design could help improve users’ memory performance and usability.

Socio-Technical Dialogue and Linguistic Interaction. Intelligent Personal Assistants (IPA) in the Private Home

Abstract The article addresses the phenomenon of voice-controlled assistance systems, or more precisely: smart speakers with voice user interfaces, as they have been finding their way into private households for some time. The public discourse revolves, among other things, around the question of the extent to which the socio-technical exchange with such systems differs from social interaction or increasingly approaches it, and, related to this, whether individual users must adapt to machines or vice versa. At the same time, empirical research shows that socio-technical dialogues and social interaction are often not two separate worlds, but components of a complex practice in which prima facie ontologically different participants are involved. These circumstances make it possible to reconstruct the characteristics of both socio-technical dialogue and the social interaction which is situated around it as linguistically mediated performances from a praxeological perspective. In this context, systematic transitions between socio-technical dialogue and a “meta-interaction space” play an important role, as do various forms of “sequential” processes and their mediation with each other. This article approaches these phenomena based on empirical data from an ongoing research project, notably audio-visual recordings of situations of the initial installation/commissioning of IPA in two- and multi-person households, audio recordings of situations of everyday use, log data of socio-technical dialogue which the systems make available to the users through the corresponding smartphone app.

Smart Assistants for Smart Living: Ideology and Mythology in AI-Powered Smart Speaker Advertising

This study examines advertising of top-selling voice-activated smart speakers in the United States to understand how advertisers are promoting these devices to consumers. The study identifies four representations of technology in smart speaker advertising. This includes technology as human, technology as self-expression and happiness, technology as progress, and technology as productivity. Engaging in semiotic analysis of select advertising, the study reveals deeper meaning, ideology, and myths in smart speaker advertising. Implications for culture and consumption are discussed.

Voice Assistants as Consultants for Male Patients with Sexual Dysfunction: A Reliable Option?

The aim of this study was to evaluate the ability of Google Assistant, Alexa, and Siri to recognize and answer questions about male sexual health. Each VA was tested on a smart speaker: Alexa on Amazon Echo Dot 4th Gen., Google Assistant on Google Home Mini, and Siri on Apple HomePod. A pool of patients' frequently asked questions regarding erectile dysfunction (ED), premature ejaculation (PE), Peyronie's disease (PD), male infertility, and other aspects of male sexual health were identified by authors. The recognition of question was evaluated ("yes" or "not"). For each recognized question, the response characteristics (domains) were rated on a scale from 0 to 10 (according to the quality). We chose the recognition rate of the questions as the primary outcome and the quality of the answers as the secondary outcome. Overall, the best VA in recognizing questions was Siri, with a total of 83.3% questions compared with 64.0% for Alexa (p = 0.024) and 74.0% for Google Assistant (p = 0.061). Siri was associated with a significantly higher recognition rate than Alexa for PE (80% vs. 40%; p = 0.002) and PD (66.7% vs. 33.3%; p = 0.010). The quality of the responses was classified as low in 57 out of 105 cases (54.3%), intermediate in 46 cases (43.8%), and high in only 2 cases (1.9%), highlighting an overall intermediate-low quality of the answers. Male infertility was the condition associated with the highest mean scores in "Targeted response to the problem" (7.32 ± 2.57), "Scientific correctness of the answer", (5.9 ± 2.76) "Completeness of the answer" (5.14 ± 2.56), and "Understandability of the response for a patient" (5.3 ± 2.51) domains. Siri was associated with significantly higher scores than Alexa (p < 0.05) in several domains of all conditions evaluated. The question recognition rate of VAs is quite high; however, the quality of the answers is still intermediate-low. Siri seems superior to Alexa in both question recognition and response quality. Male infertility appears to be the sexual dysfunction best addressed by VAs.

Will digital technology address the challenges of drug development in psychiatry?

Will digital technology address the challenges of drug development in psychiatry?

Exploratory Descriptive Analysis of Smart Speaker Utilization in the Emergency Department During the COVID-19 Pandemic

BackgroundIn March 2020, the U.S. Department of Health and Human Services Office for Civil Rights stated that they would use discretion when enforcing the Health Insurance Portability and Accountability Act regarding remote communication technologies that promoted telehealth delivery during the COVID-19 pandemic. This was in an effort to protect patients, clinicians, and staff. More recently, smart speakers—voice-activated, hands-free devices—are being proposed as productivity tools within hospitals. ObjectiveWe aimed to characterize the novel use of smart speakers in the emergency department (ED). MethodsA retrospective observational study of Amazon Echo Show® utilization from May 2020 to October 2020 in a large academic Northeast health system ED. Voice commands and queries were classified as either patient care–related or non-patient care–related, and then further subcategorized to explore the content of given commands. ResultsOf 1232 commands analyzed, 200 (16.23%) were determined to be patient care–related. Of these commands, 155 (77.5%) were clinical in nature (i.e., “drop in on triage”) and 23 (11.5%) were environment-enhancing commands (i.e., “play calming sounds”). Among non-patient care–related commands, 644 (62.4%) were for entertainment. Among all commands, 804 (65.3%) were during night-shift hours, which was statistically significant (p < 0.001). ConclusionsSmart speakers showed notable engagement, primarily being used for patient communication and entertainment. Future studies should examine content of patient care conversations using these devices, effects on frontline staff wellbeing, productivity, patient satisfaction, and even explore opportunities for “smart” hospital rooms.

CREBAS: Enabling Network Access Control in a Home with One Click

Many smart home devices, such as smart speakers, are connected to a home network. Conventional home networks do not control communications among devices, including malicious devices. As a result, malicious devices in a home network can steal private information and manipulate devices that have no or weak access control mechanisms. Some methods have been proposed to protect devices, but cannot control communications in some situations and do not discuss their authorization architecture or usability. Malicious devices can bypass access control, and users may make incorrect configurations due to their complexity. They can make access control meaningless. In this paper, we propose CREBAS, which enables network access control to protect devices from malicious or unintended communications. We propose a capability-based authorization architecture and discuss its validity according to the guidelines for access control in a home. Also, we propose methods that provide more fine-grained and stricter network access control according to authorized capabilities. We have implemented a prototype of CREBAS. The prototype has shown that the performance degradation is acceptable, and it is possible to perform access control with one click in a real protocol used in a home network.

Alexa doesn't have that many feelings: Children's understanding of AI through interactions with smart speakers in their homes

As voice-based Conversational Assistants (CAs), including Alexa, Siri, Google Home, have become commonly embedded in households, many children now routinely interact with Artificial Intelligence (AI) systems. It is important to research children's experiences with consumer devices which use AI techniques because these shape their understanding of AI and its capabilities. We conducted a mixed-methods study (questionnaires and interviews) with primary-school children aged 6–11 in Scotland to establish children's understanding of how voice-based CAs work, how they perceive their cognitive abilities, agency and other human-like qualities, their awareness and trust of privacy aspects when using CAs and what they perceive as appropriate verbal interactions with CAs. Most children overestimated the CAs' intelligence and were uncertain about the systems' feelings or agency. They also lacked accurate understanding of data privacy and security aspects, and believed it was wrong to be rude to conversational assistants. Exploring children's current understanding of AI-supported technology has educational implications; such findings will enable educators to develop appropriate materials to address the pressing need for AI literacy.

Few-Shot Speaker Identification Using Lightweight Prototypical Network With Feature Grouping and Interaction

Existing methods for few-shot speaker identification (FSSI) obtain high accuracy, but their computational complexities and model sizes need to be reduced for lightweight applications. In this work, we propose a FSSI method using a lightweight prototypical network with the final goal to implement the FSSI on intelligent terminals with limited resources, such as smart watches and smart speakers. In the proposed prototypical network, an embedding module is designed to perform feature grouping for reducing the memory requirement and computational complexity, and feature interaction for enhancing the representational ability of the learned speaker embedding. In the proposed embedding module, audio feature of each speech sample is split into several low-dimensional feature subsets that are transformed by a recurrent convolutional block in parallel. Then, the operations of averaging, addition, concatenation, element-wise summation and statistics pooling are sequentially executed to learn a speaker embedding for each speech sample. The recurrent convolutional block consists of a block of bidirectional long short-term memory, and a block of de-redundancy convolution in which feature grouping and interaction are conducted too. Our method is compared to baseline methods on three datasets that are selected from three public speech corpora (VoxCeleb1, VoxCeleb2, and LibriSpeech). The results show that our method obtains higher accuracy under several conditions, and has advantages over all baseline methods in computational complexity and model size.

Distributed Self-Localization for Acoustic Transceiver Networks

Today, we are often surrounded by a lot of acoustic transceivers, such as smartphones, tablets, and smart speakers. If they constitute an acoustic transceiver network (ATN), they can be exploited for various acoustic signal processing tasks. In this letter, we propose a decentralized frame-work for geometry calibration in ATNs. Based on direction-of-arrival (DoA) and time-difference-of-arrival (TDoA) measurements, the self-localization is first implemented in local coordinate systems from different nodes. Subsequently, a distributed consensus approach is derived, which maps these local coordinates to a common one. As a result, the inconsistency among local coordinates is eliminated, and the nodes are localized in a virtual coordinate system. Finally, numerical results validate the proposed method.

USING A SMART SPEAKER IN THE EDUCATIONAL PROCESS OF PRESCHOOLERS

Introduction of modern technologies, namely smart speakers, in preschool education is gaining relevance. The purpose of the study is to develop methodological material for teachers and parents on the use of “speakers” in all educational fi elds. Research methods include questionnaire, comparison, analysis, and observation. Sample includes parents (n=) and teachers (n=). When analyzing the parents’ questionnaire, it turned out that more than half of the respondents use speakers at home, but not all of them know what range of games the system offers. At the same time, .% of parents support the use of modern technologies within the preschool educational organization. % of respondents consider the introduction of a smart speaker in kindergarten possible. When analyzing the questionnaire of teachers, it turned out that % of respondents would like to use a smart column in classroom but only % know how to use it. The use of smart speakers in preschool organizations will undoubtedly affect the quality of education and development of the child.

Intelligent personal assistants: A brief overview

Intelligent Personal Assistants (IPA), also known as virtual or digital assistants, are software programs that utilize Artificial Intelligence (AI) and Natural Language Processing (NLP) to perform a wide range of tasks and services for users. This study provides an overview of Intelligent Personal Assistants, their capabilities, and their impact on human life. IPAs can be accessed through various devices such as smartphones, smart speakers, and smart displays, and can be activated through voice commands or graphical interfaces. The key advantage of intelligent personal assistants is their ability to understand and respond to natural language, enabling users to interact with them in a more natural and intuitive manner. In addition to executing tasks, IPAs can offer personalized information and recommendations based on user preferences and past interactions. The concept of smart advisors, which specializes in providing subject-specific advice and recommendations, was introduced. Overall, this study aims to shed light on intelligent personal assistants and address any skepticism surrounding this new age of technology, highlighting their potential to enhance and improve human lives.