Mechanism, training and limits of human echolocationLéopold Kritly1,3,David Pelegrin Garcia 2,Antoine Gademer 3, Christ Glorieux 4, Monika Rychtarikova1,5

1 Faculty of Architecture - KU Leuven 2 Widex A/S3 Institute of Systems and Electronics - EPF Montpellier 4 Laboratory of Acoustics - KU Leuven 5 Faculty of Civil Engineering - STU Bratislava

Presentation outlines

Introduction

Mechanism

Training

Limits

Perspectives

Basis

Usage

Operating cues

Introduction

Stick

Environmental noise

External help

Echolocation

20 Minutes, Phlessons,

Cité des Sciences et de l’Industrie

Introduction

V ≈ 299.8 km/s V ≈ 342 m/sX 1000

Processing of environment perception

Immediate Sound reflections arrive not at the same time

Mechanism

Ability to use sounds to locate and identify the objects aroundWhat is echolocation ?

Active Passive

Human head

Self sound emission

Direct Sound

Obstacle reflection

Propagation through environment

Echoes

Environment noise

Human head

Obstacle reflectionDirect Sound

Echoes

Propagation through environment

Pelegrin-Garcia D., Rychtarikova M., Zelem L., Chmelik V., Kritly L., Glorieux C. (2017). Can humans use echolocation to hear the difference between different kinds of walls ? ASA, 2669-2.

MechanismActive echolocation: Self sound emissions

Emission Tongue click Whistles Hisses Speech

Spectrum content Broad band Tonal Broad band Speech range

[200 : 4000] Hz

Intensity High Small

Duration Impulsive Long

Usage Polyvalent Short range & sound coloration detectionsRequired silent environment

Most used

MechanismWhat could we detect through echolocation ?

• Location

• Size

• Intrinsic features

• Shape

• Texture

Information about obstacle:

MechanismObstacle location - Distance

Time of propagation

RDLD = Lrefl – Ldir

t

t

Left ear

Right ear

p

Reflected to Direct Level Difference (RDLD)

MechanismObstacle location - Orientation / Localization

Oral-Binaural Room Impulse Response (OBRIR)

t

t

Left ear

Right ear

p Interaural delay

GitHub – CSSonar [Online] – Josh Lind – 2015

MechanismFeatures from objects recognition

Changes in spectrum (emission / emission + echoes )

Kolarik, A. J., Cirstea, S., Pardhan, S., & Moore, B. C. J. (2014). A summary of research investivating echolocation abilities of blind and sighted humans. Hearing Research, 310, 60-68. Compact Dynamics – Acoustical Material and Acoustics [Online] - http://www.12345w.xyz/compactdynamics-com/encyc-acoustics-0.html

Carpet

Fabrics

Wood

Plexiglas

C.E. Rice, S.H. Feinstein & R.J. Schusterman (1965). J.Exp.Psychol. 70, 246

MechanismMinimum detectable target size

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MechanismMinimum detectable target size

Audibility Thresholds of a Sound Reflection in a Classical Human Echolocation ExperimentPelegrin-Garcia, Rychtarikova, Glorieux - Acta Acustica United With Acustica - Vol 102 (2016) 530-539

Increase of diameter sizeo reflected level decreaseso low frequencies are

reflected more efficiently

• OBRIR meas. on disks of 4 different sizeo 5.6 cm, 11.6 cm, 23.8 cm, 38.6 cm,

• 5 different distances(case of Rice’s study)

o 0.5m, 1m, 1.5m, 2m, 2.5 m

MechanismConstitution shape recognition

Mapping of echoic informationDifficulty to recognize Shape

Easy

Medium

Hard

Kolarik, A. J., Cirstea, S., Pardhan, S., & Moore, B. C. J. (2014). A summary of research investivatingecholocation abilities of blind and sighted humans. Hearing Research, 310, 60-68.

Mesh space

• interval that contains between 0.5 and 99.5% of the energy

• thick bars contains the central 75% of the energy

• dots show the central time (same energy before and after)

MechanismTexture recognition

Reflected to Direct Level Difference (RDLD)

Temporal spread of reflections

Pelegrin-Garcia D., Rychtarikova M., Zelem L., Chmelik V., Kritly L., Glorieux C. (2017). Can humans use echolocation to hear the difference between different kinds of walls ? ASA, 2669-2.

MechanismA powerful mechanism

Cycle

Training – KU Leuven facility

Hike in nature

Ski

Seth Freeman – 2011,Wowscience – Brighter Life Experiences for Blind People with the use of echolocation [Online] - 2017,

Youtube / Poptech – Daniel Kish’s echolocation in action [Online] – 2011

• Goals of using a VR systemo Now: Better understand the underlying perceptual mechanisms o Future: Help in echolocation training and familiarization with

unknown environments

Training

VR Audioprocessor

t

t

Left ear

Right ear

p

Oral-Binaural Room Impulse Response (OBRIR)Emulation with acoustic Virtual Reality (VR)

Training

1. Audibility of sound reflections

2. Discrimination - localization

3. Feature recognition (size, shape, texture…)

4. Complex tasks – environment identification, obstacle avoidance

5. Use in daily life – integration with other mobility techniques

Sens

atio

n

Perc

eptio

n

Cog

nitio

n

The 5 layers of human echolocation

Fundamental aspects

ResearchInterest

LimitsPerformance in complex environments

o Reverberant

o Noisy

Improvable buildings design for echolocators

Wikipedia – St Andrew Church, PxHere,

Deviantart – Isstatu1

PerspectivesUnderstanding echolocation

in architectural context

Design of acoustic markers Discrimination of features

necessary for echolocation

Training of people who became

blind during their lifetime

Thank you for your attention

• Results averaged for the two ears:

Comparing real vs virtual experimentsReflected-to-direct level difference (RDLD)

• Increase of diameter sizeo reflected level decreaseso low frequencies are

reflected more efficiently

• the further one go the lower the the level of reflection is

Comparing real vs virtual experimentsReflected-to-direct level difference (RDLD)

• Single number RDLDo Frequency weighting: “typical oral click” + inverted loudness level curve

from ISO-226:2003o Uncertainty of ~3 dB due to reference click choice and anatomical

differences

Comparing real vs virtual experimentsReflected-to-direct level difference (RDLD)

• Rice et al.’s (1965) thresholds revised

• RDLD Threshold: -20 dB independent of distance

• +/- 3 dB spread across participants

• Use as reference performance

That’s how we can translate thresholds vs solid angle.

Comparing real vs virtual experimentsReflected-to-direct level difference (RDLD)

That’s how we can translate thresholds vs solid angle.

RDLD, as a function of the distance to the obstacle =the equivalent time delay of the reflection

black = average

gray symbols = individual results

error bars ± 1 standard deviation

horizontal gray bold lineaverage RDLD correspondingto a constant solid anglecovered by the target

Sensitivity to a single reflectionResults

• Click durationo Exp. I: Pre-recorded sounds 3.1 mso Exp. II: Self-generated sounds 12 ms

RDLD thresholds lower with distance (but also do reflection levels!)

Longer clicks worse thresholdsVariability in “click” production more spread in thresholds

Masking is non-linear louder clicks result in better thresholds

/s/-like sounds only effective at short distances

Thresholds for blind echolocators ~ 10 dB better at short distances(compare only black filled symbols)• Better signals?• More trained to detect coloration?• Inhibition from direct sound?

RDLD of stimuli• conditions at 1.5m are above thresholds,

except for the wall 7 and 12• conditions at 10 m are much further from threshold

than at 1.5 m.