Auditory Navigation Performance is Affected by Waypoint ...sonify.psych.gatech.edu/publications/pdfs/2004ICAD... · Undergraduates from the Georgia Institute of Technology participated

Proceedings of ICAD 04 - The Tenth International Conference on Auditory Display, Sydney, Australia, July 6-9, 2004

Auditory Navigation Performance is Affected by Waypoint Capture Radius

Bruce N. Walker and Jeff Lindsay

Sonification Lab, School of PsychologyGeorgia Institute of Technology

654 Cherry Street NWAtlanta, GA, USA 30332-0170

[email protected] , [email protected]

ABSTRACT

Non-speech audio navigation systems can be very effectivemobility aids for persons with either temporary orpermanent vision loss. Sound design has certainly beenshown to be important in such devices [e.g. 1]. In this studywe consider the added factor of capture radius. The captureradius of an auditory beacon is defined as the range at whichthe system considers a user to have reached the waypointwhere the beacon is located. 108 participants successfullynavigated paths through a virtual world using only non-speech beacon cues. Performance differed across the captureradius conditions. Further, there was a speed-accuracytradeoff, which complicates the design decision process.Implications of these results for the design of auditorynavigation aids are discussed, as are other ongoing andfuture studies.

1. INTRODUCTION

When visual information is not available, either due topermanent vision loss or to temporary conditions such assmoke or darkness, the fundamental task of navigatingthrough our environment can become a major challenge.Technological solutions involving auditory displays maybe able to assist a wide range of users in the non-visualnavigation task, but there are many unanswered questionsregarding the best ways to present assistive informationthrough an auditory interface, as well as how to design thehuman-system interaction. Walker and Lindsay [1] describedthe results of an initial study aimed at determining the bestauditory beacons to be used in audio navigation aids. In thepresent paper we provide an update to that initial report,including expanded data and additional conclusions, and wediscuss new and ongoing investigations in the developmentof an effective auditory navigation system.

There are approximately 11.4 million people with visionloss in the United States. Of this population, ten percenthave no usable vision; and by 2010 these numbers willnearly double [2]. The prevalence of blindness rises steadilywith age to the extent that nearly two-thirds of people withvision loss are 65 years of age or older [3, 4]. This rise in theaverage age of people with severe visual impairment is theresult of the increase in average age of the generalpopulation, and the increased prevalence of diabeticretinopathy, macular degeneration and glaucoma in thiscountry. Just as everyone else, visually impairedindividuals wish to lead an active, independent life whichincludes freely moving about the community, runningerrands, shopping, working, and taking advantage of theservice and entertainment opportunities in theirenvironment.

In addition to persons with vision loss, there are wholeclasses of persons who have normal vision but for whomtemporary smoke, fog, darkness, fire, or other environmentalconditions prevent them from seeing their immediatesurroundings, and can lead to disorientation and aninability to navigate from place to place. Firefighters in asmoke-filled building may not be able to locate thestairwell; military personnel in darkness or under water maynot be able to reach a particular rendezvous location; policein the midst of a protest may lose orientation due to thicktear gas. Also, even when people can see, during some tasksthey may be unable to use vision for navigation since it isrequired for another concurrent task. Broadly, then, thegroups of individuals who can benefit from auditorynavigation interfaces can be summarized as those whocannot see and those who cannot look.

1.1. Prior Investigation

There are several systems that have been developed that usesound to help persons with vision loss through anenvironment. They have typically been designed for personswith visual impairments One representative system is thePersonal Guidance System (PGS) [5, 6]. The PGS interfaceconsists of a virtual 3D auditory environment where acomputer creates spatialized speech beacons such that theperceived location of the beacon is at the place that thesemantic content in the beacon refers (e.g. “Doorway here” asan auditory beacon).

However, non-speech audio cues are important toconsider because there are several drawbacks to usingexclusively speech sounds. First, speech beacons are harderto localize in a virtual audio environment than non-speechbeacons [7]. Users also give speech beacons low ratings forquality and acceptance [7]. Second, the speech-basedinterface cannot display a large amount of information, astwo or more speech beacons presented simultaneously aredifficult to attend to, given the limited human speechprocessing capacity [e.g., 8]. It would also most certainly notbe possible to use the speech-based interface and carry on aconversation at the same time [e.g., 9]. Third, spokenmessages in such a system are each generally more than asecond long, so the system is often talking. Thisinefficiency of speech can result in a cluttered and annoyinglistening environment.

As a result of these findings, our own auditorynavigation projects have focused on non-speech audio.Walker and Lindsay [1] evaluated different beacon soundsfor use in a navigation aid, based on the findings of Tran etal. [7]. Specifically, Tran et al. studied a number of sounds(both speech and non-speech) to be used in navigation aidsand concluded that a wide-band, non-speech sound was mosteffective. The sonar-like sound they used was indicated as


the best out of their stimulus set. Walker and Lindsay [1]determined that a broadband noise beacon was, indeed, themost effective for their navigation task. In that study,however, the sonar-like sound was actually the worstperformer. These results parallel the findings of Lokki,Grohn, Svioja, and Takala [10], in which a (pink) noisesource was found to be more effective than musicalinstrument sounds in moving through a virtual world. Thusit seems that beacon sound does have an effect onnavigation effectiveness, but it is likely the general natureof the sound (e.g., broadband), and not the specific soundthat should be considered as paramount.

In the course of the work reported by Walker andLindsay [1] there were naturally questions that remained tobe explored. In particular, issues were raised about how theuser would actually move from waypoint to waypoint alonga path. In the world of computerized navigation aids eachwaypoint is specified by exact x, y, and z coordinates.However, in the course of moving towards and past onewaypoint, and heading on to the next one, the preciselocation of the user might never actually coincide exactlywith the waypoint, despite having passed pretty much rightover it. A computer system might say that the user failed totraverse the path correctly, since she never technicallyarrived at the penny-sized point. A human observer would,on the other hand, say she was definitely “close enough” toeach of the points. This is the concept of capture radius.That is, there is a radius around the waypoint that i sconsidered close enough, so that the next beacon sound canappear, and the user can carry on down the next pathsegment. If the capture radius is too small, the user mayovershoot the waypoint, and may walk past the corner, offthe sidewalk, and into the street. If the capture radius is toolarge, the person may be told she has reached the turningpoint too soon, and as a result either cut across the grass orrun into a building on the corner. Thus, to keep the personon the intended path—neither missing the marks norturning too soon—an optimal capture radius needs to bedetermined. In the work described here we present an updateand extension of the previous study, focusing exclusivelyon capture radius as it affects navigation success with anauditory display.

2. EXPERIMENTAL INVESTIGATION

We set out to study just how precisely the listeners couldmaneuver along a path using our audio navigation system,and how it was affected by varying the capture radius of thewaypoints that defined the path.

2.1. Participants

Undergraduates from the Georgia Institute of Technologyparticipated for partial course credit. All reported normal orcorrected-to-normal vision and hearing. There were a total of108 participants (71 male, 37 female; mean age 20.2, range18 to 30). Note that a small subset of these data werediscussed in [1]. The present data includes data from 69 newparticipants, and includes an additional level of the captureradius factor (the middle capture radius is entirely new,here).

2.2. Apparatus

As before, our audio navigation studies were conductedusing a virtual reality-based testing environment,constructed using the Simple Virtual Environments (SVE)

software package developed by the College of Computing atthe Georgia Institute of Technology [11]. The beacon soundswere played through closed ear headphones. To changedirection participants rotated on the spot where they weresitting. They used two buttons on a joystick to controlforward and backward movement in the VR environments(they did not actually walk forward, they were only requiredto rotate in place). Their orientation within the environmentwas tracked by an Intersense InertiaCube 2 head-mountedtracking cube attached to the headphones.

Each participant was asked to navigate three differentpaths in the VR world. The VR environment in which thesepaths (or maps) were located was essentially a large empty(virtual) room with four plain walls and a simple tiled floor(recall, there is no need for any visual fidelity, since theparticipant only has an auditory interface). In addition to thestarting point, Map 1 had five waypoints and Maps 2 and 3each had 10 waypoints. The three maps differed simply inthe layout of the waypoints. The visual rendering of thespace, including cubes to mark the waypoints, was availableto the experimenter to monitor a participant’s progressthrough the map. The SVE software logged the participant’slocation in the environment (in terms of X, Y, and Zcoordinates), head orientation (angular pitch, yaw, and roll),and the waypoint she was currently moving towards, every 2ms.

Even though it is not a focus of the present discussion(and analyses are collapsed across this variable), it i simportant to point out that there were different beaconsounds involved in the full study design. The participantswere divided into three groups, with each group beingguided through the maps by a different navigation beaconsound. The beacon sounds for all three groups were 1 s long,with a center frequency of 1000 Hz and equal loudness. Thesounds differed greatly in timbre, however. The first soundbeacon was a burst of broadband noise centered on 1 kHz.The second beacon was a pure sine wave with a frequency of1 kHz. The third beacon sound was a sonar pulse, similar tothe sound that Tran el al. [7] found to be one of the bestsounds for use as a navigation beacon. Thus, eachparticipant navigated using the same sound throughouttheir three maps. At the start of a map the beacon soundplayed in an on-off pattern, where the sound was on for 1 sand off for 1 s of silence. As the listener moved closer to thenext waypoint the silence was shortened to effectively makethe beacon tempo faster. Hence, increasing proximity to thewaypoint was mapped to increasing tempo, which isconsistent with our findings for population stereotypes orpreferred mappings between proximity and tempo [12].

We were primarily interested in examining how preciselya listener can navigate such an auditory environment withdifferent capture radii for the waypoints. Thus, withineachbeacon-sound group, one third of the participants had asmall (50 cm) capture radius, one third had a medium (1.5 m)capture radius, and the final third had a large (15 m) captureradius. Thus, the beacon sound and capture radius wereconstant throughout the three maps for a given participant.These different beacon radii were chosen based on the resultsof earlier pilot testing. In practice, as a participant reached awaypoint (or, rather, got close enough to be within thecapture radius), a “success” chime sounded and the beaconsound moved in space so as to lead the listener towards thenext waypoint in the map. It did not matter from whichdirection the user approached a waypoint; simply gettingwithin the capture radius was sufficient. So if a participantmissed a waypoint, then turned around and came back to thewaypoint, the waypoint could be reached successfully fromthe “wrong” side. Of course, this would mean that the personhad moved some extra distance and wasted time, which i s


reflected in the efficiency and rate calculations for that map.For the large capture radius the participant might actuallynot come very close to the real waypoint, given the broadregion that was “close enough”.

2.3. Procedure

Participants were welcomed and the task was explained insome detail. In particular, the techniques for movingthrough the map and the concept of a front-back confusionwere discussed. A brief questionnaire was administered togather demographic information and informed consent wasobtained. Once the study began, participants moved through

the three maps one after the other, with a brief rest betweenmaps. The map order was the same for all participants.Following completion of the third map, the experimenterexplained the purpose of the study, answered any questions,and thanked the participant.

3. RESULTS

Clearly there are a number of ways to consider the results ofsuch a large study with several variables to consider. For thepresent paper we will focus only on the findings relevant toour question of capture radius. Full discussion of thecomprehensive analysis can be found elsewhere [13]. Wefirst considered the global question of whether participantswould be able to complete the navigation tasks using onlynon-speech auditory cues. Figure 1 presents the movementtraces of participants for all three capture radii, whennavigating through the second map, and with the noisebeacon. These particular results are shown because they arerepresentative and instructive; results for the first and thirdmaps, and for the other beacon sounds are very similar. Thestraight dark solid line between the waypoints represents thescheduled path, and the other lines in each panel representthe different paths traveled by the participants. The firstresult to note is the relatively successful navigation throughthe map by nearly all participants. Not only couldparticipants complete the maps, they picked up the task veryquickly and with little instruction. Nevertheless, it i simportant to note that in some cases there are significantdepartures from the scheduled path. Most often these resultfrom a participant walking just past a waypoint and notrealizing it for some time because the beacon sound is mis-localized as coming from the front instead of from the rear(i.e., an overshoot exacerbated by front-back confusion).This navigation error occurs most often with the smallestcapture radius. In the top panel of Figure 1 (the smallestcapture radius) several of the waypoints have a “star-like”pattern of movement traces around them. This is the result ofa participant overshooting the waypoint, turning around andheading back towards it, then overshooting again. Thishunting behavior does not appear nearly as often for themedium capture radius, and is very rare for the largestcapture radius.

The second result to note is the difference between thegeneral movement patterns in the different capture radiusconditions. In the smallest capture radius condition theparticipants stick very close to the scheduled path, and passprecisely over the waypoints enroute. There is a sort of“pinch point” at each waypoint that is very small for thesmall radius (naturally). In the larger two capture radiusconditions the pinch point is more relaxed, and if a personstrays off the scheduled path, he or she need not comeexactly back to the path in order to carry on—the captureradius allows some flexibility (or “slop”, depending onone’s perspective) in the path. For the medium radius theparticipants seem to move off the path in some cases, butstill come back to the waypoint.

Finally, in the largest capture radius condition, theparticipants often never even reach the actual waypoint.They come close enough for the capture radius to besatisfied, but their overall path is actually quite different,geometrically, from the scheduled path. The turning anglesare often considerably more or less acute than the angles inthe path they were supposed to travel. Certainly the severityof this depends on the context and the reasons for which theperson is traversing the path. For practical purposes, themedium capture radius has a compromise between relatively

Noise Beacon - Map 2 - Small Radius

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Figure 1. Movement traces for participants in Map 2, withthe noise beacon, and all three capture radius conditions.

Note the overall navigation success, and the variabilitybetween conditions.


little overshooting and hunting, and relatively closepassage by the waypoints.

At this point we turned to a more quantitative analysisof the rate of completion and the path length efficiency inthe various conditions. We analyzed the data using a mixedfactors multivariate analysis of variance (MANOVA). Thebetween-subjects factors were the beacon sound used and thecapture radius. The within-subjects factor was map number.The dependent measures being recorded for each map werethe participant’s overall completion rate (time through themap divided by map length) and their navigation efficiency(total distance traveled divided by scheduled map length).We define the scheduled map length as the sum of thelengths of the shortest-distance path segments. That is, if aperson moved directly from waypoint to waypoint towaypoint in a map, she would travel a distance equal to thescheduled length. Since participants typically veered off theshortest path somewhat and in some cases overshot thewaypoints, the actual distance the participants traveled wasusually (but not always) longer than the scheduled maplength. The “extra” distance they traveled can be consideredas wasted time and effort, and we predicted that comparingthe distance the person was supposed to travel to thedistance they actually followed would be a useful metric ofthe movement efficiency afforded by the different beaconsounds and capture radii. This efficiency metric can also beviewed as an indicator of how effective the map might be inguiding a visually impaired person along a specific path(e.g., along a sidewalk). With this in mind, deviation fromthe path could potentially be very dangerous if there wereenvironmental hazards near the path (e.g. roads, a ditch, etc.).Thus, a priori we assumed an optimal efficiency score wouldbe 100 percent, indicating that for the most part theparticipant stayed very close to the scheduled map route. Inthe multivariate analyses we used Wilks’ Lambda todetermine F values, and throughout all analyses we set analpha level of .05.

In terms of capture radius, the MANOVA on thecombined dependent variables revealed a significant effectof the capture radius being employed, F(4, 196) = 63.67, p <.001, Wilks’ Lambda = .19. This significant multivariateeffect led us to seek further clarification in the results for thetwo dependent variables considered separately.

There was a main effect of capture radius on both rate,F(2, 99) = 29.07, p < .001, and efficiency, F(2, 99) = 24.16, p< .001. These results are presented in Figure 2. In the case ofrate (Figure 2, left panel), overall the largest capture radius(15 m) yielded the fastest completion rate (1.44), the

medium capture radius (1.5 m) led to the slowest rate (0.75),and the smallest capture radius (0.5 m) led to an intermediaterate (1.08). In the case of efficiency, however, the results arequite different (see Figure 2, right panel). The largest captureradius led to a moderate efficiency (88.1%), while themedium capture radius led to the greatest efficiency(105.8%), and the smallest radius led to the lowest efficiency(72.5%). Note that efficiency can be greater than 100% sincethe implementation of a capture radius makes it possible totraverse a path that is actually shorter than the scheduledmap length. Taken together, these two results for rate andefficiency are analogous to a speed-accuracy tradeoff. Forexample, in the case of the medium capture radius theparticipants were slow but very efficient. Participants usingthe large capture radius were fast but inefficient. That is, theyspent less time orienting themselves to the beacon sounds,and subsequently traversed a longer path than necessary.However, the large capture radius was very “forgiving”, andas a result they were still able to complete the maps quickly.The importance of these various strategies will be discussedshortly.

4. DISCUSSION

There are several important ideas to be drawn from theresults presented here. The first and most important is thatthe non-speech auditory interface can definitely be used forsuccessful navigation. Participants were able to follow thepaths in the virtual environment using only the spatializedbeacon sounds. Their ability to do so is well illustrated bythe traces in Figure 1. Even in the least effective cases,participants strayed relatively little from the pathdesignated by the beacons. This successful performanceamongst almost all individuals is a good indicator that theinterface can be successful. This is important since thelikelihood of simultaneous conversation, use of radio ormobile telephone, or other speech communication points tothe need for a non-speech navigation system. In the fewcases where a participant’s path did deviate significantlyfrom the beacon path, it was most often due to overshootinga beacon by passing just outside its capture radius. Oncethat happened the participant might have experienced frontback confusion and did not turn around to find the beaconbecause it still sounded as if it was ahead of them. This canlead to a dramatic departure from the planned route, so i tmust not be dismissed. In debriefing participants it seemsclear that some listeners just do not seem to “get” theinterface, and never really navigate very well. It may be

Effect of Capture Radius on Rate

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Figure 2. Effect of capture radius on completion rate and efficiency. The main effect indicates the equivalent of a speed(rate) – accuracy (efficiency) tradeoff in performance.


important to isolate what leads to such confusion with thenavigation cues. However, we should be clear that theseinstances are quite rare, in our experience. Most people pickup the task immediately, show good performance from thestart, and improvements with practice. We have consideredthat the overshoot likelihood is exacerbated by the smallercapture radius. Thus, given that some participants will missthe target waypoint sometimes, we have considered a numberof ways to make passing by the waypoint more salient.Studies of a variety of waypoint passing and front-backdisambiguation methods are currently underway and will bereported separately.

Next, the effect of capture radius on performance foundhere appears to be more practically significant than that ofbeacon sound. Tran et al. [7] investigated the effectivenessof various types of beacon sounds, but did not considerother potentially important factors. Capture radius was alsonot a main focus of Walker and Lindsay [1]. The results ofthe present study provide evidence that while sound designshould certainly be considered and evaluated carefully, thereare additional critical aspects.

Finally, this study also highlights the differencebetween theoretical and real world considerations. Since forour application we are primarily designing for visuallyimpaired individuals, safety (or remaining on the path) is aparamount concern. There is an obvious speed-accuracytradeoff occurring between rate and efficiency for differentcapture radii. Given that fact, and given our primary concernfor accuracy, we would first look at the capture radius thatled to the best efficiency, and then consider other factorsthat may affect rate as the situation permits. In a real worldapplication it does not matter if a person using this type ofsystem to navigate down the sidewalk does not move quiteas quickly, so long as he or she can manage to remain on thesidewalk throughout the path. Thus, as is often the case, atrue human-centered approach must be taken in order toavoid “optimizing” the system at the expense of the user.

Of course, the development of a non-speech auditoryinterface of this type remains a work in progress. Since suchan interface is novel for all users, in addition to the generaleffects of interface design elements we are beginning tostudy the effectiveness of different training methods onperformance. This includes an evaluation of the basiclearnability of different interface sounds and the mosteffective types of training. Further, it is not clear whetherthere are individual differences in the perception,understanding, and learning of auditory displays (speech ornon-speech), nor how one might predict performance withsuch a system. Also, to our knowledge, none of the speech-based navigation systems to date involves context- or task-dependent adjustments to the information that is presented.The needs of the listener, within her present acoustical andfunctional environment, must be factored in so the interfacecan adapt appropriately. For example, if a user is on target toa waypoint 30 meters down a straight hall, with no obstaclesin the way, then the system should stay relatively quiet andlet the person use the mobility skills she already has.Approaching the target, the system can gracefully chime inagain. A related issue is communicating to the listener thedegree of certainty about location, orientation, and items inthe surroundings. Knowing that there is some uncertainty inthe location (perhaps due to relying solely on GPS) i simportant for the user in order to adjust attention and othermovement techniques. In the present virtual reality-basedtests of the interface, the exact location is known, and thelistener need not rely on any other sensory input forguidance. Certainly, it will be interesting to see thesimilarities and differences in effectiveness of the interfacewhen used in an actual movement situation (i.e., not in the

VR environment). As the result of pilot studies and our ownexperience with the outdoor version of our system (whichuses a wearable computer), we are confident that thelocalization of the beacons and the interaction with thesystem remains similar, and the overall navigation remainsrobust. We do, however, see some differences in the actualmovement style that the users employ. For example, we havenoticed that outdoors users tend to walk a little bit moreslowly than without the system. However, this effectdiminishes with continued usage and increased confidence.Similarly in the virtual environment, participants tend toengage in a type of stop and go pattern of motion that is notnecessarily typical of normal movement. Once again thislessens as familiarity with the system increases. Also, i tremains to be studied how effectively a user can navigatewith an auditory wayfinding system, while at the same timecompleting other cognitive tasks such as decision makingand planning. This multitask proficiency will be importantfor success of any system aimed at assisting in navigation.Finally, and perhaps most importantly, we are presentlyconducting several of these listening and navigation studieswith low vision and blind participants. Clearly this is acrucial group for comparison with the results reported thusfar. As Walker and Lane [14] observed, there are manysimilarities, but often notable differences in the wayparticipants with visual impairments react and respond towhat they hear. This is especially true when it comes tonavigation without vision. Preliminary results of thesestudies seem to indicate that severely visually impaired andblind users, including elderly individuals, are able to usethe system at or near the same proficiency level as thesighted undergraduates if they are given sufficient trainingand practice.

In summary, we have shown the effectiveness of non-speech auditory beacons in guiding a listener along a path,and have highlighted the importance of considering bothsound design and other interaction aspects such as captureradius that affect the performance of users in an auditory-only navigation task. Current and future additional studiesinvolving both sighted and visually impaired participants,are also considered.

5. REFERENCES

[1] B. N. Walker and J. Lindsay, "Effect of beacon soundson navigation performance in a virtual realityenvironment," Proceedings of Ninth InternationalConference on Auditory Display ICAD2003, Boston,MA, 2003.

[2] W. De l’Aune, Legal Blindness and Visual Impairmentin the Veteran Population 1990-2025. Decatur, GA: VARehabilitation R&D Center, 2002.

[3] National Center for Veteran Analysis and Statistics,National Survey of Veterans: Assistant Secretary forPolicy and Planning, Department of Veterans Affairs,Gov’t Printing Office, 1994.

[4] G. L. Goodrich, Growth in a Shrinking Population:1995-2010. Palo Alto, CA: Palo Alto Health CareSystem, 1997.

[5] J. Loomis, R. Golledge, R. Klatzky, J. M. Speigle, and J.Tietz, "Personal guidance system for the visuallyimapired," Proceedings of First Annual InternationalACM/SIGCAPH Conference on Assistive Technologies(ASSETS94), Marina del Rey, CA, 1994.

[6] J. Loomis, C. Hebert, and J. G. Cicinelli, "Activelocalization of virtual sounds," Journal of the


Acoustical Society of America, vol. 88, pp. 1757-1764,1990.

[7] T. V. Tran, T. Letowski, and K. S. Abouchacra,"Evaluation of acoustic beacon characteristics fornavigation tasks," Ergonomics, vol. 43, pp. 807-827,2000.

[8] G. H. Mowbray and J. W. Gebhard, "Man's senses asinformational channels," in Human factors in thedesign and use of control systems, H. W. Sinaiko, Ed.New York: Dover, 1961, pp. 115-149.

[9] C. D. Wickens, Engineering psychology and humanperformance, 2nd ed. New York, NY: HarperCollinsPublishers, 1992.

[10] T. Lokki, M. Grohn, L. Savioja, and T. Takala, "A casestudy of auditory navigation in virtual acoustic

environments," Proceedings of internationalConference on Auditory Display (ICAD2000), Atlanta,GA, 2000.

[11] GVU Virtual Environments Group, "SVE Toolkit," vol.2000, 1997.

[12] B. N. Walker, "Stability of magnitude estimation forauditory data representations," in preparation.

[13] B. N. Walker and J. Lindsay, "Navigation performancewith a virtual auditory display: Effects of beaconsound, capture radius, and practice," under review.

[14] B. N. Walker and D. M. Lane, "Psychophysical scaling ofsonification mappings: A comparision of visuallyimpaired and sighted listeners," Proceedings of 7thInternational Conference on Auditory Display, Espoo,Finland, 2001.

Acknowledgments. This research was partly funded by a Training Grant from the VA Atlanta Rehabilitation R&D Center.

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Auditory Navigation Performance is Affected by Waypoint ...sonify.psych.gatech.edu/publications/pdfs/2004ICAD... · Undergraduates from the Georgia Institute of Technology participated