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LiveSnippets: Voice-based Live Authoring of Multimedia Articles about Experiences
- Source :
- MobileHCI
- Publication Year :
- 2020
- Publisher :
- ACM, 2020.
-
Abstract
- We transform traditional experience writing into in-situ voice-based multimedia authoring. Documenting experiences digitally in blogs and journals is a common activity that allows people to socially connect with others by sharing their experiences (e.g. travelogue). However, documenting such experiences can be time-consuming and cognitively demanding as it is typically done OUT-OF-CONTEXT (after the actual experience). We propose in-situ voice-based multimedia authoring (IVA), an alternative workflow to allow IN-CONTEXT experience documentation. Unlike the traditional approach, IVA encourages in-context content creations using voice-based multimedia input and stores them in multi-modal “snippets”. The snippets can be rearranged to form multimedia articles and can be published with light copy-editing. To improve the output quality from impromptu speech, Q&A scaffolding was introduced to guide the content creation. We implement the IVA workflow in an android application, LiveSnippets - and qualitatively evaluate it under three scenarios (travel writing, recipe creation, product review). Results demonstrated that IVA can effectively lower the barrier of writing with acceptable trade-offs in multitasking.
- Subjects :
- 050101 languages & linguistics
Multimedia
Multimedia authoring
Computer science
media_common.quotation_subject
05 social sciences
02 engineering and technology
Content creation
computer.software_genre
Impromptu
Workflow
Documentation
0202 electrical engineering, electronic engineering, information engineering
Travel writing
Human multitasking
020201 artificial intelligence & image processing
0501 psychology and cognitive sciences
Quality (business)
computer
media_common
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services
- Accession number :
- edsair.doi...........101771a8d7ff20e5252516f520ff4ecf
- Full Text :
- https://doi.org/10.1145/3379503.3403556