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User Requirements in
Audiovisual Search
A Quantitative Approach
Danish Nadeem
Roeland Ordelman
Robin Aly
Erwin Verbruggen
AUDIOVISUAL ARCHIVE
BUSINESS ARCHIVE
DUTCH PUBLIC BROADCASTERS
DIGITIZATION
CLARIAH PRESENTATIE 11 September 2013 5
800.000 hrs
?METADATA
Document level
vs
Segment level
CLARIAH PRESENTATIE 11 September 2013 8
TOOLS
9
USEFUL?
Developer/
ICT researcher
User
CLARIAH PRESENTATIE 11 September 2013 10
FEEDBACK
Access to
Audiovisual
Archives
Content
Technology
User Requirements in Audiovisual Search: a Quantitative Approach
ARCHIVAL METADATA
SUBTITLES
AUDIO ANALYSIS:
SPEECH/SPEAKER RECOGNITION
pose
beach
Luther King
Obama
Visual analysis
AUDIOVISUAL SEARCH
VIDEO HYPERLINKING
Broadcast professionals
Broadcast
Professionals
Re-use
Media Archivists Annotate
Research & Education
Broadcast
Professionals
Hergebruik
Media Archivists
(documentalisten)
Beschrijven
Journalists Research
Academic researchers Investigate
Education Illustrate
Home user
Public Entertainment
Edutainment
21
Use Scenarios
&
System
Requirements
Interview
&
elicitation
sessions
Mock-up
creation &
evaluation
Prototype
evaluation
System
evaluation
Surveys &
log analysis
Qualitative
Qualitative
QualitativeQuantitative
Quantitative/
Qualitative
Quantitative approach
• Categorization of user requirements
• According to different user groups
• Prioritize implementation of system features
1. 2. 3.
Concept Mapping
• Data collection
• Multidimensional Scaling
• Hierarchical Cluster Analysis
Method
• Phase 1: “Idea generation”
–Caveat: unfamiliarity with A/V search
–Interviews, requirements elicitation
experiments using system mock-ups
–professionals, researchers, home user
–71 “statements”
Method (2)
• Phase 2: “Sorting & Rating”
–47 participants, evenly spread over 3 groups
–Categorize according to perceived similarity
• Create categories and label with description
–Rate according to desirability
• 1-5: undesirable – highly desirable
Categories vizualisation
Categories
User-defined search functions
Translates into:
1. having options for search manipulation and
result representation:
– change sort order of results (date, relevance)
– Use filters and activate them at any point during
search
– Use boolean operators
2. the system should be clear and guide users in
a rather complex search process
Advanced search
• Users are eager to make use of advanced search
options:
– Search using example image
– Events, persons, speakers, visual objects
– Using multiple metadata sources, e.g.,
• Archival metadata
• Speech transcripts
• Visual labels
• Less interest in “technical” metadata
– Shot types, camera movement, b/w-color
Help functions
• Slight miss-alignment with what developers
understand as “help functions”
• Next to “access to help manuals”:
– System should be fast
– Clear, user-friendly, intuitive UI
– Access to video
– Clear message when no results are found
– Consistent results
USER GROUP COMPARISON
User Requirements in Audiovisual Search: a Quantitative Approach
User Requirements in Audiovisual Search: a Quantitative Approach
DEVELOPMENT IMPLICATIONS
PRO
RESEARCH
HOME
User Requirements in Audiovisual Search: a Quantitative Approach
User Requirements in Audiovisual Search: a Quantitative Approach
Conclusions
• Quantitative approach using concept mapping
– Useful approach to get some more grip on user
requirements and differences between user
groups
– Helps to steer development process of advanced
user type specific A/V search tools
– User defined labels may not always be in-line with
formal definitions used by developers which may
cause confusions, e.g.,
• Help functions vs. clear, smooth and consistent system
Conclusions (2)
• Clear interest of users in
1. advanced search options
2. segment-level access points to AV by means of
rich multi-modal annotations (speech, speakers,
events, objects)
3. Clear, transparent, smoothly working system
Upcoming
STUDY
HOME USERS
&
VIDEO HYPERLINKING
@
BBC
http://www.axes-project.eu
Information Retrieval for
Information Services
http://www.project-infiniti.nl/

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User Requirements in Audiovisual Search: a Quantitative Approach

Editor's Notes

  • #15: Automatic annotations