Articulate+: An Always Listening Interface for Creating Data Visualizations

Simple item page
dc.contributor.advisorLeigh, Jason
dc.contributor.authortabalba, roderick S.
dc.contributor.departmentComputer Science
dc.date.accessioned2023-02-23T23:56:51Z
dc.date.available2023-02-23T23:56:51Z
dc.date.issued2022
dc.description.degreeM.S.
dc.identifier.urihttps://hdl.handle.net/10125/104621
dc.subjectComputer science
dc.subjectAlways Listening Interface
dc.subjectArticulate+
dc.subjectArtificial Intelligence
dc.subjectData Visualization
dc.subjectNatural Language Processing
dc.subjectVoice User Interface
dc.titleArticulate+: An Always Listening Interface for Creating Data Visualizations
dc.typeThesis
dcterms.abstractDigital assistants are becoming more frequently used in our daily lives. We use Alexa to turn off the lights, Siri to play music, and Cortana to check the weather. These systems allow users to complete daily tasks, but are we utilizing these systems to their full potential? Current research and technology in Voice User Interfaces (VUIs) are constantly improving the way we interact with digital assistants, but are required to only start listening once the user starts addressing the system. This requirement potentially limits what these systems can accomplish for the user. We should be including these systems in our conversation so that they can start participating in our discussions and meetings by suggesting new ideas or proposing new topics just as a human assistant would do. This would enable digital assistants to become collaborators and co-pilots in our life, rather than merely tools. In my thesis, I will discuss my investigation into collaborative digital assistants by examining Natural Language Interfaces (NLIs) that facilitate data exploration tasks. I created Articulate+, an always listening system that generates data visualizations all through voice commands. Articulate+ presents a digital persona of itself, called Arti, designed to act as a collaborator. I developed an always listening method that leverages conversational data to generate informative data visualizations. I conducted a user study in order to evaluate Articulate+ and investigate the benefits of my always listening method. My contributions in this thesis will bring us one step closer to a future where AI will be able to participate in meetings and discussions just as a human would.
dcterms.extent73 pages
dcterms.languageen
dcterms.publisherUniversity of Hawai'i at Manoa
dcterms.rightsAll UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.
dcterms.typeText
local.identifier.alturihttp://dissertations.umi.com/hawii:11560

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
tabalba_hawii_0085O_11560.pdf
Size:
3.08 MB
Format:
Adobe Portable Document Format
Download

Collections

M.S. - Computer Science