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A Document Skimmer
Overcoming the soda-straw effect
Alex Krstic
Kelly Van Busum
Suzanne Vogel
Outline
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Problem Overview
Prior Work (briefly)
Our Work
Demo
Study
Follow up
Overview: Problem
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Listening is slower than reading, but
speeding up decreases comprehension
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Speed up only by increasing reading rate,
with NO scanning or skimming
Skip ahead only by one line or one page
Overview: Goal
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Identify features to increase speed
Enable the user to adjust these features
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Trade off speed and comprehension
Prior Work: Features
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Scan at levels of detail (LODs)
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Skip 1 segment within a level
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Speech Skimmer [1] & Aster [2]
Speech Skimmer [1]
Refs
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2.
Speech Skimmer (Arons, 1993)
Aster (Raman, 1994)
Prior Work: Implementation
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Segment document, semantically
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Speech divisions: Long pauses [1]
Text divisions: Structure boundaries [2]
Filter out words or sounds within
segments
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Spaces [1]
Latter P number of words or seconds [1]
Detailed (lower-level) info [2]
Our Work: Features
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Hierarchy
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Dropping Words/Phonemes
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Spatial Sound
Our Work: LOD Hierarchy
Our Work: Dropping Words/Sounds
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Dropping common words
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Change text to phonemes
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Remove phonemes without lexical stress
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toz, suhn
computing  mpyootng
Blending phonemes (Drop spaces)
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what up  whuhtuhp
Our Work: Spatial Sound
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Hearing more than one sound source at
the same time
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2, 3 or 4
Each source plays different segments of
the file
Some sources dominant over the others
Spatial orientation
Our Work: Screenshot
Copyright 2003, ASK (Alex, Suzanne, Kelly)
User Evaluations
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3 informal, 4 systematic
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Asked questions, navigate to answer
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Hear text in various forms, then asked
questions
User Evaluations, 2
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Hierarchy
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Sound (Word) Removal
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Difficult to explain “hierarchy concept”, underused
Removing common words was liked (29% of words)
Either really liked or hated phonemes (29%, 10%)
Spatial Sound
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2 sounds worked ok, 3 or more didn’t
*Lots of different perspectives!
New Questions…
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How much does voice selection matter?
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How much would training help?
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What is the relationship between phonemes and speed?
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What is the role of prior knowledge?
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How does this relate to Ctrl-F?
Acknowledgements
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Peter Parente
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Pointed us to programming resources (BATS;
wxPython, Python Numeric 22.0, Win32
libraries)
Gave us Python sample code for speech
synthesis and spatial sound
Experiment participants
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(Informed consent requires confidentiality)
Programming Resources
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BATS NCDemo – http://www.sourceforge.net
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OpenAL.dll, MSVRTD.dll, pyTTS.py, pyOpenAL.py (I
think)
Python – http://www.python.org/
Win32 library for Python –
http://starship.python.net/crew/mhammond/
Python Numeric 22.0 library –
http://www.pfdubois.com/numpy/
wxPython GUI library – http://www.wxpython.org/