Date: | April 1st, 2009 |
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Location: | DC 1331 |
Time: | 1:30 |
Chair: | Kate Kinnear |
Date: | April 8th, 2009 | April 15th, 2009 | April 22nd, 2009 | April 29th, 2009 |
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Location: | DC 1331 1:30 | DC 1331 1:30 | DC 1331 1:30 | DC 2303 1:30 |
Chair: | Ben Lafreniere |
Stephen Mann |
Michael McCool |
Zainab Meraj |
Technical Presentation: | Craig Kaplan |
Kate Kinnear |
Ben Lafreniere |
Stephen Mann |
Martin Talbot |
Title : On the Audio Representation of Distance for Blind Users
Abstract: This study examines methods for displaying distance information to blind travellers using sound, focussing on abstractions of methods currently used in commercial Electronic Travel Aids (ETAs). Ten blind participants assessed three sound encodings commonly used to convey distance information by ETAs: sound frequency (Pitch), Ecological Distance (ED), and temporal variation or Beat Rate (BR). Response time and response correctness were chosen for measures. Pitch variation was found to be the least effective encoding, which is a surprise because most ETAs encode distance as Pitch. Tempo, or BR, encoding was found to be superior to Pitch. ED, which was simulated by filtering high frequencies and decreasing intensity with distance, was found to be best. Grouping BR and ED redundantly slightly outperformed ED. Consistent polarity across participants was found in ED and BR but not in Pitch encoding. |
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2009 Apr 01, 13:30 - Algorithms and Complexity Group Seminar Periklis Papakonstantinou, University of Toronto A hierarchy between P and RP
2009 Apr 01, 16:30 - Distinguished Lecture Series Seminar Nancy Leveson, Massachusetts Institute of Technology Computers and Trust
2009 Apr 02, 10:30 - Computer Science Seminar Martin Bravenboer, University of Massachusetts Amherst Software Development Challenges: Abstraction and Analysis
2009 Apr 03, 11:30 - Artificial Intelligence Lab Seminar Jesse Hoey (University of Dundee, Scotland) Intelligent Devices to Engage Cognitively Disabled Older Adults in Visual Artwork
2009 Apr 03, 14:00 - Bioinformatics Group PhD Seminar Christina Ann Boucher, PhD Candidate, David R. Cheriton School of Computer Science, University of Waterloo Detecting motifs in a large data set: applying probabilistic insights to motif finding
Also see other Math and CS postings.