Relevant bibliographies by topics / Amazon Alexa

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Amazon Alexa'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 April 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Amazon Alexa.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Amazon Alexa"

1

Barceló-Armada, Rubén, Ismael Castell-Uroz, and Pere Barlet-Ros. "Amazon Alexa traffic traces." Computer Networks 205 (March 2022): 108782. http://dx.doi.org/10.1016/j.comnet.2022.108782.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Lopatovska, Irene, Katrina Rink, Ian Knight, Kieran Raines, Kevin Cosenza, Harriet Williams, Perachya Sorsche, David Hirsch, Qi Li, and Adrianna Martinez. "Talk to me: Exploring user interactions with the Amazon Alexa." Journal of Librarianship and Information Science 51, no. 4 (March 7, 2018): 984–97. http://dx.doi.org/10.1177/0961000618759414.

Full text
Abstract:
Amazon Alexa is a voice-controlled application that is rapidly gaining popularity. We examined user interactions with this technology, and focused on the types of tasks requested of Alexa, the variables that affect user behaviors with Alexa, and Alexa’s alternatives. The data about Alexa usage were collected from 19 participants via the online questionnaire and diary methods over the course of several days. The results indicate that across all age groups, Alexa was primarily used for checking weather forecasts, playing music, and controlling other devices. Several participants reported using Apple Siri and Google Now applications in addition to Alexa for similar purposes except for controlling other devices. Alexa uses over the weekends were more frequent than on weekdays, but its overall usage tended to decrease over time. The users reported being satisfied with Alexa even when it did not produce sought information, suggesting that the interaction experience is more important to the users than the interaction output. More work is required to understand whether users treat Alexa and similar voice-controlled applications as primarily a traditional information retrieval system, a casual leisure system, a control interface for smart home devices, or, simply, a new toy.
APA, Harvard, Vancouver, ISO, and other styles
3

Chung, Hyunji, Jungheum Park, and Sangjin Lee. "Digital forensic approaches for Amazon Alexa ecosystem." Digital Investigation 22 (August 2017): S15—S25. http://dx.doi.org/10.1016/j.diin.2017.06.010.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

West, Emily. "Amazon: Surveillance as a Service." Surveillance & Society 17, no. 1/2 (March 31, 2019): 27–33. http://dx.doi.org/10.24908/ss.v17i1/2.13008.

Full text
Abstract:
This essay argues that Amazon, the leading e-commerce platform in many parts of the world, uses surveillance not just as a key tool in the platform logic of its growing constellation of businesses but also increasingly as a service to its consumers. In contrast to prevailing assumptions that platforms will obscure the surveillant aspects of their businesses and that users will resist the intrusive nature of corporate surveillance, Amazon’s business practices point to the rapid normalization, and even embrace, of surveillant logics by consumers. Given the importance of consumer data to its operations, Amazon increasingly designs services whose purpose is, at least in part, to collect more data about consumers. The zenith of Amazon’s surveillance capabilities of its customers is no doubt its family of Echo devices enabled by the artificial intelligence interactive-voice service Alexa, which connects to the cloud run by Amazon, itself, through Amazon Web Services. Alexa is similar to competing digital voice assistants like Apple’s Siri and Google’s Assistant, but with more cultural visibility, worldwide market penetration, and greater integration with a host of Internet-of-Things devices produced by a variety of manufacturers. Amazon seeks to make Alexa an indispensable service to consumers, one that sweetens the granular forms of surveillance in more private spaces and situations that it now has the capability to gather, relative to the company’s more established forms of surveillance. While a typical association with surveillance might be the alienation and disempowerment of social control, I suggest that Amazon’s practices of consumer surveillance cultivate a sense of intimacy, borne of being seen between consumer and brand. In other words, I advocate for recognizing the subjectification of contemporary practices of platform surveillance, in addition to its structural elements.
APA, Harvard, Vancouver, ISO, and other styles
5

Major, David, Danny Yuxing Huang, Marshini Chetty, and Nick Feamster. "Alexa, Who Am I Speaking To?: Understanding Users’ Ability to Identify Third-Party Apps on Amazon Alexa." ACM Transactions on Internet Technology 22, no. 1 (February 28, 2022): 1–22. http://dx.doi.org/10.1145/3446389.

Full text
Abstract:
Many Internet of Things devices have voice user interfaces. One of the most popular voice user interfaces is Amazon’s Alexa, which supports more than 50,000 third-party applications (“skills”). We study how Alexa’s integration of these skills may confuse users. Our survey of 237 participants found that users do not understand that skills are often operated by third parties, that they often confuse third-party skills with native Alexa functions, and that they are unaware of the functions that the native Alexa system supports. Surprisingly, users who interact with Alexa more frequently are more likely to conclude that a third-party skill is a native Alexa function. The potential for misunderstanding creates new security and privacy risks: attackers can develop third-party skills that operate without users’ knowledge or masquerade as native Alexa functions. To mitigate this threat, we make design recommendations to help users better distinguish native functionality and third-party skills, including audio and visual indicators of native and third-party contexts, as well as a consistent design standard to help users learn what functions are and are not possible on Alexa.
APA, Harvard, Vancouver, ISO, and other styles
6

Phan, Thao. "Amazon Echo and the Aesthetics of Whiteness." Catalyst: Feminism, Theory, Technoscience 5, no. 1 (April 1, 2019): 1–38. http://dx.doi.org/10.28968/cftt.v5i1.29586.

Full text
Abstract:
This article examines the figuration of the home automation device Amazon Echo and its digital assistant Alexa. While most readings of gender and digital assistants choose to foreground the figure of the housewife, I argue that Alexa is instead figured on domestic servants. I examine commercials, Amazon customer reviews, and reviews from tech commentators to make the case that the Echo is modeled on an idealized image of domestic service. It is my contention that this vision functions in various ways to reproduce a relation between device/user that mimics the relation between servant/master in nineteenth- and twentieth-century American homes. Significantly, however, the Echo departs from this historical parallel through its aesthetic coding as a native-speaking, educated, white woman. This aestheticization is problematic insofar as it decontextualizes and depoliticizes the historic reality of domestic service. Further, this figuration misrepresents the direction of power between user and devices in a way that makes contending with issues such as surveillance and digital labor increasingly difficult.
APA, Harvard, Vancouver, ISO, and other styles
7

Liverpool, Layal. "Audio attack blocks Amazon Alexa from hearing you." New Scientist 244, no. 3256 (November 2019): 12. http://dx.doi.org/10.1016/s0262-4079(19)32141-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Wellsandt, Stefan, Mina Foosherian, and Klaus-Dieter Thoben. "Interacting with a Digital Twin using Amazon Alexa." Procedia Manufacturing 52 (2020): 4–8. http://dx.doi.org/10.1016/j.promfg.2020.11.002.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Sorensen, Katelyn, and Jennifer Johnson Jorgensen. "“Hey Alexa, Let's Shop”." International Journal of E-Services and Mobile Applications 13, no. 1 (January 2021): 1–14. http://dx.doi.org/10.4018/ijesma.2021010101.

Full text
Abstract:
Millennials quickly adapt to new technologies and have been found to use voice technology daily. This study follows the technology acceptance model (TAM) developed by Davis to explain the relationships between perceived ease of use (PEOU), perceived usefulness (PU), perceived enjoyment (PE), and perceived innovativeness (PI) to behavioral intention (BI) for Millennials. An online survey generated 204 usable responses through Amazon Mechanical Turk. Multiple regression analyses supported the relationship of PEOU to PU, PU, PE, PI to BI, and PEOU was not found to influence BI in this study. The findings of this study indicate that consumers are ready to purchase through voice-activated technologies, but the current platform needs to be adapted so that it is easier to use.
APA, Harvard, Vancouver, ISO, and other styles
10

Hooda, Ashish, Matthew Wallace, Kushal Jhunjhunwalla, Earlence Fernandes, and Kassem Fawaz. "SkillFence." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, no. 1 (March 29, 2022): 1–26. http://dx.doi.org/10.1145/3517232.

Full text
Abstract:
Voice assistants are deployed widely and provide useful functionality. However, recent work has shown that commercial systems like Amazon Alexa and Google Home are vulnerable to voice-based confusion attacks that exploit design issues. We propose a systems-oriented defense against this class of attacks and demonstrate its functionality for Amazon Alexa. We ensure that only the skills a user intends execute in response to voice commands. Our key insight is that we can interpret a user's intentions by analyzing their activity on counterpart systems of the web and smartphones. For example, the Lyft ride-sharing Alexa skill has an Android app and a website. Our work shows how information from counterpart apps can help reduce dis-ambiguities in the skill invocation process. We build SkilIFence, a browser extension that existing voice assistant users can install to ensure that only legitimate skills run in response to their commands. Using real user data from MTurk (N = 116) and experimental trials involving synthetic and organic speech, we show that SkillFence provides a balance between usability and security by securing 90.83% of skills that a user will need with a False acceptance rate of 19.83%.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Amazon Alexa"

1

Liu, Purong. "Voice Control of Fetch Robot Using Amazon Alexa." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/97439.

Full text
Abstract:
With the rapid development of computers and technology, virtual assistants (VA) are becoming more and more common and intelligent. However, virtual assistants, such as Apple's Siri, Amazon's Alexa, and Google Assistant, do not currently have any physical functions. As an important part of the internet of things (IoT), the field of robotics has become a new trend in the usage of VA. In this project, a mobile robot, Fetch, is connected with the Amazon Echo Dot through the Amazon web service (AWS) and a local robot operation system (ROS) bridge server. We demonstrated that the robot could be controlled by voice commands through an Amazon Alexa. Given certain commands, Fetch was able to move in a desired direction as well as track and follow a target object. The follow model was also learned by Neural Network training, which allows for the target position to be predicted in future maps.
Master of Science
Nowadays, virtual personalized assistants (VPAs) exist everywhere around us. For example, Siri or android VPAs exist on every smartphone. More and more people are getting household Virtual Assistants, such as Amazon Alexa, Google Assistant, and Microsoft's Cortana. If the virtual assistants can connect with objects which have physical functions like an actual robot, they will be able to provide better services and more functions for humans. In this project, a mobile robot, Fetch, is connected with the Echo dot from Amazon. This connection allows us to control the robot by voice command. You can ask the robot to move in a given direction or track and follow a certain object. In order to let the robot learn how to predict the position of the target when the target is lost, a map is built as an influence factor. Since a designed algorithm of target position prediction is difficult to implement, we opted to use a machine learning method instead. Therefore, a machine learning algorithm was tested on the following model.
APA, Harvard, Vancouver, ISO, and other styles
2

Wang, Jiamin. "Measuring the Functionality of Amazon Alexa and Google Home Applications." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/97316.

Full text
Abstract:
Voice Personal Assistant (VPA) is a software agent, which can interpret the user's voice commands and respond with appropriate information or action. The users can operate the VPA by voice to complete multiple tasks, such as read the message, order coffee, send an email, check the news, and so on. Although this new technique brings in interesting and useful features, they also pose new privacy and security risks. The current researches have focused on proof-of-concept attacks by pointing out the potential ways of launching the attacks, e.g., craft hidden voice commands to trigger malicious actions without noticing the user, fool the VPA to invoke the wrong applications. However, lacking a comprehensive understanding of the functionality of the skills and its commands prevents us from analyzing the potential threats of these attacks systematically. In this project, we developed convolutional neural networks with active learning and keyword-based approach to investigate the commands according to their capability (information retrieval or action injection) and sensitivity (sensitive or nonsensitive). Through these two levels of analysis, we will provide a complete view of VPA skills, and their susceptibility to the existing attacks.
M.S.
Voice Personal Assistant (VPA) is a software agent, which can interpret the users' voice commands and respond with appropriate information or action. The current popular VPAs are Amazon Alexa, Google Home, Apple Siri and Microsoft Cortana. The developers can build and publish third-party applications, called skills in Amazon Alex and actions in Google Homes on the VPA server. The users simply "talk" to the VPA devices to complete different tasks, like read the message, order coffee, send an email, check the news, and so on. Although this new technique brings in interesting and useful features, they also pose new potential security threats. Recent researches revealed that the vulnerabilities exist in the VPA ecosystems. The users can incorrectly invoke the malicious skill whose name has similar pronunciations to the user-intended skill. The inaudible voice triggers the unintended actions without noticing users. All the current researches focused on the potential ways of launching the attacks. The lack of a comprehensive understanding of the functionality of the skills and its commands prevents us from analyzing the potential consequences of these attacks systematically. In this project, we carried out an extensive analysis of third-party applications from Amazon Alexa and Google Home to characterize the attack surfaces. First, we developed a convolutional neural network with active learning framework to categorize the commands according to their capability, whether they are information retrieval or action injection commands. Second, we employed the keyword-based approach to classifying the commands into sensitive and nonsensitive classes. Through these two levels of analysis, we will provide a complete view of VPA skills' functionality, and their susceptibility to the existing attacks.
APA, Harvard, Vancouver, ISO, and other styles
3

De, Lisa Angelo. "SensorSpeak: monitoraggio e controllo vocale di reti di sensori mediante Amazon Alexa." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14555/.

Full text
Abstract:
L’Internet of Things (IoT) sta rapidamente acquistando una grande importanza e utilità nella vita di tutti i giorni. L’idea di base dell’IoT è la presenza pervasiva, intorno a noi, di oggetti in grado di interagire e di cooperare tra loro per eseguire una determinata funzione. Con il proliferare di nuove applicazioni e tecnologie in tale ambito, si introducono anche innovativi modi di collaborare e interagire, sia dal punto di vista degli oggetti che dell’uomo. Essendo la voce la maniera naturale dell’uomo di esprimersi, l’integrazione del controllo vocale nei sistemi IoT offre un metodo versatile ed intuitivo in termini di interazione, comunicazione e controllo dei dispositivi. Lo scopo di questa tesi è la realizzazione di SensorSpeak, un sistema di monitoraggio e controllo dei dispositivi IoT mediante l’utilizzo di comandi vocali. Attraverso la semplice interazione vocale con Amazon Alexa, l’utente è in grado di monitorare e controllare i dispositivi associati al proprio cloud. L’approccio utilizzato nell’implementazione del sistema estende il suo utilizzo ad un’enorme varietà di dispositivi e la sua integrazione in diversi scenari, come smart home o reti di sensori. Inoltre, data l’importanza della questione energetica in contesti del genere, è stato testato un algoritmo di predizione del tempo di carica rimanente delle batterie che alimentano i device. SensorSpeak è stato installato e testato in una rete 6LoWPAN montata presso il centro di ricerca ARCES di Bologna per il monitoraggio dei sensori disposti all’interno della struttura.
APA, Harvard, Vancouver, ISO, and other styles
4

Werlinder, Marcus, and Emelie Tham. "Application of Amazon Web Services in software development." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231917.

Full text
Abstract:
During these last recent years cloud computing and cloud services have started to gain traction, which has been most notable among companies. Amazon have proven to be one of the powerhouses on providing scalable and flexible cloud computing services. However, cloud computing is still a relatively new area. From an outsider’s point of view, the overwhelming information and available services might prove to be difficult to familiarize with. The aim of this thesis is to explore how Amazon Web Services can be applied during software development and observing how difficult it might be to use these services. Three test applications that utilized different Amazon Web Services were implemented to get an insight into how Amazon Web Services can be applied from a cloud computing beginner’s point of view. These applications were developed in an iterative manner, where a case study was performed on each application. At the start of each new iteration a literature study was conducted, where sources were reviewed to see if it provided essential information. In total, nine different Amazon Web Services were used to implement and test the three respective test applications. Results of the case study were interpreted and evaluated with regards to the learnability and appliance of Amazon Web Services. Issues that were identified during the development process showed that Amazon Web Services were not userfriendly for users that have little to no experience with cloud computing services. Further research on other Amazon Web Services, such as Elastic Cloud Computing, as well as other cloud computing platforms like Google or IBM, may provide a deeper and more accurate insight on the appliances of cloud computing.
Under dem senaste åren så har molntjänster blivit ett allt mer populärt område, speciellt inom företag. Ett av dem största utgivare inom molntjänst branschen är Amazon som erbjuder skalbara och flexibla molntjänster. Molntjänster är dock ett relativt nytt område, vilket innebär att någon som inte är insatt i ämnet kan finna all tillgänglig information överväldigande och svår att bekanta sig med. Målet med det här tesen är att utforska olika Amazon Web Service som kan användas inom mjukvaruutveckling och observera problem som kan uppstå med dessa tjänster. Tre testapplikationer som använde sig av Amazon Web Services var skapade för att få en fördjupad kunskap om hur dessa tjänster fungerar och vad för möjligheter de har. Dessa applikationer utvecklades iterativt och en fallstudie utfördes för varje applikation. I början av varje ny iteration genomfördes en litteraturstudie, där källorna var kritiskt granskade för att se ifall dem innehöll väsentlig information för tesen. Sammanlagt användes nio olika Amazon Web Services för att implementera och testa de tre olika testapplikationerna. Resultaten från fallstudien tolkades och utvärderades med avseende på Amazon Web Services lärbarhet och tillämpningsbarhet. Problem som samlades ihop under utvecklingsprocessen visade att Amazons Web Services inte var särskilt användarvänligt för utvecklare med liten eller ingen erfarenhet inom Amazon Web Services. Ytterligare forskning inom andra Amazon Web Services som Elastic Cloud Computing och forskning som undersöker andra molntjänst plattformar som Google Cloud, skulle kunna bidra med en djupare förståelse och mer exakt inblick kring tillämpning av molntjänster.
APA, Harvard, Vancouver, ISO, and other styles
5

Layden, Caroline A. "Relationship Between Intelligibility and Response Accuracy of the Amazon Echo in Individuals with Amyotrophic Lateral Sclerosis Exhibiting Mild-Moderate Dysarthria." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7325.

Full text
Abstract:
There is an ever-growing and increasing amount of technology options that use speech recognition software. Currently, the market includes smartphones, computers, and individual smart home personal assistants that allow for hands-free access to this technology. Research studies have explored the utility of these assistive devices for the completion of activities of daily living; however, there is limited research looking at the accuracy of voice recognition software within smart home personal assistants in populations with disordered speech. In persons with amyotrophic lateral sclerosis (ALS), symptoms include changes to motor functions, speech in particular, and it is unknown how some of these devices may respond to their disordered speech. The present study aimed to examine the accuracy of the Amazon Echo to respond appropriately to commands given by dysarthric patients with ALS. Participants were asked to read a variety of commands to an Amazon Echo. The sentences and responses by the Amazon Echo were audio-recorded for transcription and intelligibility ratings, which were then analyzed to look for relationships between intelligibility, auditory-perceptual features of speech, and sentence type. Results revealed there was no significant relationship between command intelligibility and accuracy of response by the Amazon Echo, nor was there a significant relationship between any of the auditory-perceptual ratings and accuracy of response. There was, however, a significant and positive association between conversational intelligibility and accuracy of responses by the Amazon Echo. This study provides support for use of hands-free assistive technology in patients with ALS to aid in the maintenance of quality of life and activities of daily living.
APA, Harvard, Vancouver, ISO, and other styles
6

Pecorelli, Margherita. "Studio e sviluppo di interfacce conversazionali a supporto di persone con disabilità: un prototipo integrato su Alexa." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20473/.

Full text
Abstract:
Negli ultimi anni si è assistita ad un'evoluzione sul modo in cui l'uomo interagisce con la macchina. Da interazioni di tipo meccanico facenti uso di tastiera e mouse si è prima passati all'utilizzo di schermi sensibili al tatto e più recentemente alla possibilità di poter comunicare oralmente con dispositivi elettronici. In questo lavoro si considerano le interfacce conversazionali con particolare riferimento al modo in cui esse potrebbero migliorare la vita di persone affette da disabilità. Si inizia analizzando in primis le tecnologie esistenti che consentono di realizzare interfacce conversazionali, per poi focalizzarsi su una delle più diffuse: Amazon Alexa. Viene in seguito realizzato un prototipo di assistente virtuale da posizionare all'ingresso del Campus Universitario di Cesena la cui funzione primaria è assistere gli utenti, fungendo da punto informazioni. Lo scopo del prototipo è quello di esplorare se questi nuovi modi di interazione uomo-macchina siano idonei per migliorare l'esperienza quotidiana di utenti con e senza disabilità. A tal fine, nel prototipo si sono integrate funzionalità di ricerca informazioni circa la struttura fisica del luogo, gli eventi in esso disponibili e i servizi erogati dalla struttura. Il lavoro discute le fasi di raccolta dei requisiti, progettazione dell'architettura, design di dettaglio e affronta anche aspetti implementativi. A seguito della realizzazione pratica del prototipo, il suo funzionamento è stato sottoposto a test, tramite utilizzo ed interviste ad utenti. I test hanno dato un esito generalmente positivo ed hanno evidenziato alcune limitazioni correnti sia del prototipo che della piattaforma che ne consente il funzionamento. Il lavoro si conclude quindi con una discussione circa i possibili sviluppi futuri da apportare al prototipo e, più in generale, sulle prospettive future degli assistenti virtuali.
APA, Harvard, Vancouver, ISO, and other styles
7

Incerti, Federica. "Preservice Teachers’ Perceptions of Artificial Intelligence Tutors for Learning." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1585088861453228.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Lindstål, Tim, and Daniel Marklund. "Application of LabVIEW and myRIO to voice controlled home automation." Thesis, Uppsala universitet, Signaler och System, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-380866.

Full text
Abstract:
The aim of this project is to use NI myRIO and LabVIEW for voice controlled home automation. The NI myRIO is an embedded device which has a Xilinx FPGA and a dual-core ARM Cortex-A9processor as well as analog input/output and digital input/output, and is programmed with theLabVIEW, a graphical programming language. The voice control is implemented in two differentsystems. The first system is based on an Amazon Echo Dot for voice recognition, which is acommercial smart speaker developed by Amazon Lab126. The Echo Dot devices are connectedvia the Internet to the voice-controlled intelligent personal assistant service known as Alexa(developed by Amazon), which is capable of voice interaction, music playback, and controllingsmart devices for home automation. This system in the present thesis project is more focusingon myRIO used for the wireless control of smart home devices, where smart lamps, sensors,speakers and a LCD-display was implemented. The other system is more focusing on myRIO for speech recognition and was built on myRIOwith a microphone connected. The speech recognition was implemented using mel frequencycepstral coefficients and dynamic time warping. A few commands could be recognized, includinga wake word ”Bosse” as well as other four commands for controlling the colors of a smart lamp. The thesis project is shown to be successful, having demonstrated that the implementation ofhome automation using the NI myRIO with two voice-controlled systems can correctly controlhome devices such as smart lamps, sensors, speakers and a LCD-display.
APA, Harvard, Vancouver, ISO, and other styles
9

Brandt, Viktor, and Jesper Olofsson. "Undersökning av flexibel implementation för hantering av multipla rösttjänster." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165854.

Full text
Abstract:
Att välja vilken eller vilka röststyrningstjänster man som företag vill stödja kan i dagens läge vara ett svårt val att göra. Det kan även var så att man inte har resurser att göra två olika implementationer. I den här undersökningen tittar vi på om det finns ett bra sätt att göra en implementation som kan hantera fler än en röststyrningstjänst. Tjänsterna vi har fokuserat på i undersökningen är Amazon Alexa och Google Assistant.
APA, Harvard, Vancouver, ISO, and other styles
10

Shehaj, Orgest. "Un sistema di Smart Retail basato su Riconoscimento Espressivo e dispositivi Beacon BLE." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13723/.

Full text
Abstract:
Lo scopo di questo lavoro di tesi è quello di proporre un nuovo ed innovativo sistema di smart retail. In particolare, questo sistema, cerca di sostituirsi alla figura del commesso, migliorando l’esperienza offerta da quest’ultimo, e lo fa analizzando le caratteristiche e le espressioni facciali dei clienti. Caratteristiche come l’età, il sesso, gli stati d’animo, la direzione della testa, della vista e la posizione del cliente. Grazie a una telecamera montata su un raspberry pi, viene fatto la profilazione degli utenti che si trovano davanti la telecamera, ogni secondo. Utilizzando il riconoscimento facciale ed emotivo, si individua l’età, il sesso e anche le preferenze del cliente analizzando i suoi stati d’animo. Abbiamo creato un applicazione android, ad hoc, che utilizza almeno 3 beacon bluetooth low energy per individuare la posizione indoor del cliente, grazie alla tecnica della trilaterazione, e calcola la percentuale di acquisto del cliente sugli oggetti che quest’ultimo osserva. E stato utilizzato l’algoritmo di classificazione Naive Bayes per calcolare la percentuale di acquisto del cliente. Il sistema tiene conto anche delle caratteristiche dei clienti che hanno acquistato in passato, e propone delle eventuali offerte o sconti, sull’articolo interessato, qualora queste dovessero convincere il cliente ad acquistare l’articolo. Il sistema proposto migliora le esperienze di shopping dei consumatori ma porta anche numerosi vantaggi ai rivenditori poichè offre una migliore gestione aziendale, riduce i cosi del rivenditore e, infine, porta una maggiore redditività aziendale. Questo sistema è stato pensato per qualsiasi tipo di attività commerciale, sia virtuale che fisica.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Amazon Alexa"

1

Mark, Greenberg, ed. Amazon diary: Property of Alex Winters. New York: Putnam, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Mark, Greenberg, ed. Amazon diary: Property of Alex Winters. New York: Putnam & Grosset Group, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Talbott, Hudson. Amazon diary: [the jungle adventures of Alex Winters]. London: Viking/Puffin, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Spy: A thriller. New York: Atria Books, 2006.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Tom, Badgett, ed. Official Sega Genesis and Game Gear strategies, 2ND Edition. Toronto: Bantam Books, 1991.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Sandler, Corey. Official Sega Genesis and Game Gear strategies, 3RD Edition. New York: Bantam Books, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Styles, Logan. Alexa : 3 Manuscripts : How to Program Alexa, Amazon Echo Dot User Guide, and Amazon Echo Dot: Programming your Alexa App. CreateSpace Independent Publishing Platform, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Amazon Echo and Alexa User Guide: The Ultimate Amazon Echo Device and Alexa Voice Service Manual Tutorial. Mihails Konoplovs, 2015.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Adams, Alexa. Alexa: 1001 Tips and Tricks How To Use Your Amazon Alexa devices. CreateSpace Independent Publishing Platform, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

STEPHEN, Jaden. Amazon Alexa Guide Book 2020: A Guidebook to Take Charge of Your Amazon Alexa Speakers with Actual Screen Shots to Assist Even a Beginner Will Boss Alexa Easily... . Independently Published, 2020.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Amazon Alexa"

1

Pandey, Avinash Chandra, Saksham Raj Seth, and Mahima Varshney. "Sarcasm Detection of Amazon Alexa Sample Set." In Lecture Notes in Electrical Engineering, 559–64. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2553-3_54.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Reddy, Thrishma, Gautam Srivastava, and Vijay Mago. "Testing the Causal Map Builder on Amazon Alexa." In Trends and Innovations in Information Systems and Technologies, 449–61. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45688-7_46.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Grover, Lakshay, V. B. Kirubanand, and Joy Paulose. "Smart Car – Accident Detection and Notification Using Amazon Alexa." In Internet of Things (IoT), 391–407. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37468-6_21.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Xie, Fuman, Yanjun Zhang, Hanlin Wei, and Guangdong Bai. "UQ-AAS21: A Comprehensive Dataset of Amazon Alexa Skills." In Advanced Data Mining and Applications, 159–73. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95405-5_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Pathak, Pankaj, Rati Shukla, Himani Jain, Vikash Yadav, Parashu Ram Pal, and Rishabh. "Amazon Alexa and Its Challenges to Reach More Households." In Lecture Notes in Networks and Systems, 1–12. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9756-2_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Ayala-Chauvin, Manuel, Fernando Saá, Fernando Villarroel-Córdova, and Albert de la Fuente-Morato. "System for Monitoring and Controlling Industrial Lighting with Amazon Alexa." In Advances in Intelligent Systems and Computing, 473–82. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72660-7_45.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Carvajal, Luis, Luis Quesada, Gustavo López, and Jose A. Brenes. "Developing a Proxy Service to Bring Naturality to Amazon’s Personal Assistant “Alexa”." In Advances in Intelligent Systems and Computing, 260–70. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60366-7_25.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Ramadan, Zahy, Maya Farah, and Hadi Audi. "The Advent of the Voice Moment of Truth: The Case of Amazon’s Alexa." In Advances in National Brand and Private Label Marketing, 165–74. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18911-2_21.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Obari, Hiroyuki, and Stephen Lambacher. "Improving the English skills of native Japanese using artificial intelligence in a blended learning program." In CALL and complexity – short papers from EUROCALL 2019, 327–33. Research-publishing.net, 2019. http://dx.doi.org/10.14705/rpnet.2019.38.1031.

Full text
Abstract:
A constructivist approach to language learning can motivate students by activating their brains to create new knowledge and reflect more consistently and deeply on their language learning experience. The present study focused on assessing the use of the Artificial Intelligence (AI) speakers Google Home Mini and Amazon Alexa as part of a Blended Learning (BL) environment to improve the English skills of two groups of native Japanese undergraduates. The participants were 47 native speakers of Japanese, all third-year business majors at a private university in Tokyo. Pretest and posttest Test of English for International Communication (TOEIC) scores, as well as results from a post-training survey, were used in evaluating the overall effectiveness of the program. Gains in TOEIC scores indicated the BL program incorporating AI speakers improved the students’ overall English skills, particularly listening comprehension. The results suggest the integration of AI, along with social media and 21st-century skills, may be an effective way to improve the English language proficiency of adult L2 learners.
APA, Harvard, Vancouver, ISO, and other styles
10

Bouguettaya, Abdelmalek, Hafed Zarzour, Ahmed Kechida, and Amine Mohammed Taberkit. "Machine Learning and Deep Learning as New Tools for Business Analytics." In Advances in Business Information Systems and Analytics, 166–88. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-9016-4.ch008.

Full text
Abstract:
Data scientists need to develop accurate and effective tools and techniques to handle a huge amount of data. Therefore, machine learning and deep learning algorithms have come to the life, especially with the impressive advances in both hardware and software fields. Many impressive existing services are helping us in our daily lives, such as Google Assistant, Uber, Alexa, and Siri, which are based on big data, machine learning, and deep learning. Although intelligent algorithms and big data have been adopted in many modern business intelligence and analytics applications, in this chapter, the authors aim to present the basics of machine learning and deep learning concepts and their utilization in the field of business intelligence. As concrete examples, with the high spread of the COVID-19 pandemic, Tesla and Amazon achieved the biggest revenue ever, where many other companies suffer. These high revenues could be due to the strategic decisions of their leaders, which are based especially on artificial intelligence.
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Amazon Alexa"

1

Lopatovska, Irene, and Harriet Williams. "Personification of the Amazon Alexa." In the 2018 Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3176349.3176868.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Durski, Sara, Wolfgang Müller, Sandra Rebholz, and Ute Massler. "Reading Fluency Training with Amazon Alexa." In 12th International Conference on Computer Supported Education. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0009568201390146.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Lit, Yanyan, Sara Kim, and Eric Sy. "A Survey on Amazon Alexa Attack Surfaces." In 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2021. http://dx.doi.org/10.1109/ccnc49032.2021.9369553.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Gao, Yang, Zhengyu Pan, Honghao Wang, and Guanling Chen. "Alexa, My Love: Analyzing Reviews of Amazon Echo." In 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, 2018. http://dx.doi.org/10.1109/smartworld.2018.00094.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Sadavarte, Sanket Sanjay, and Eliane Bodanese. "Pregnancy Companion Chatbot Using Alexa and Amazon Web Services." In 2019 IEEE Pune Section International Conference (PuneCon). IEEE, 2019. http://dx.doi.org/10.1109/punecon46936.2019.9105762.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Krueger, Clemens, and Sean McKeown. "Using Amazon Alexa APIs as a Source of Digital Evidence." In 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). IEEE, 2020. http://dx.doi.org/10.1109/cybersecurity49315.2020.9138849.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Aranibar Villegas, Kevin J., José M. Veliz Francia, and Alfredo Barrientos Padilla. "Desarrollo de un In-Room Entertainment System con Amazon Alexa." In Décima Segunda Conferencia Iberoamericana de Complejidad, Informática y Cibernética. Winter Garden, Florida, United States: International Institute of Informatics and Cybernetics, 2022. http://dx.doi.org/10.54808/cicic2022.01.140.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Du, Yao, Kerri Zhang, Sruthi Ramabadran, and Yusa Liu. "“Alexa, What is That Sound?” A Video Analysis of Child-Agent Communication From Two Amazon Alexa Games." In IDC '21: Interaction Design and Children. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3459990.3465195.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Bispham, Mary, Ioannis Agrafiotis, and Michael Goldsmith. "Nonsense Attacks on Google Assistant and Missense Attacks on Amazon Alexa." In 5th International Conference on Information Systems Security and Privacy. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007309500750087.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Kepuska, Veton, and Gamal Bohouta. "Next-generation of virtual personal assistants (Microsoft Cortana, Apple Siri, Amazon Alexa and Google Home)." In 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2018. http://dx.doi.org/10.1109/ccwc.2018.8301638.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Amazon Alexa' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography