Kaytetye coronal contrasts without...

Kaytetye coronal contrasts withoutcontours

Susan Lin, Benjamin Davies, and Katherine Demuthsusan.lin@mq.edu.au

ARC Centre for Excellence in Cognition and its DisordersMacquarie University

October 6, 2013Ultrafest VIEdinburgh

Kaytetye coronal contrasts withoutedge-detection

Susan Lin, Benjamin Davies, and Katherine Demuthsusan.lin@mq.edu.au

ARC Centre for Excellence in Cognition and its DisordersMacquarie University

October 6, 2013Ultrafest VIEdinburgh

IntroductionProcedures

Results

Ultrasound in practiceA place for qualitative observations?Kaytetye coronal contrast: a test case

Why use ultrasound?

Benefits

I Good spacial resolution

I Reasonable temporal resolution (and improving!)

I Portability

I Immediacy of visual information

Consequence

Portable ultrasound machines are being employed in fieldwork anddocumentation, in increasing numbers.

Results

Why use ultrasound?

Benefits

I Good spacial resolution

I Reasonable temporal resolution (and improving!)

I Portability

I Immediacy of visual information

Consequence

Portable ultrasound machines are being employed in fieldwork anddocumentation, in increasing numbers.

Results

Typical procedures

1. Collect

2. Post-processI Extract relevant framesI Edge-detection of contours

3. Analyze

4. Interpret

Post-processing may be time-consuming

I Infrastructure cost (in time) high for small projects and/orprojects with simple questions

I Processing time may be too high for performing while on site

Results

Typical procedures

1. Collect

2. Post-process

I Extract relevant framesI Edge-detection of contours

3. Analyze

4. Interpret

Results

Typical procedures

1. Collect

3. Analyze

4. Interpret

Results

Typical procedures

1. Collect

3. Analyze

4. Interpret

Results

Typical procedures

1. Collect

3. Analyze

4. Interpret

Results

Typical procedures

1. Collect

3. Analyze

4. Interpret

Results

Typical procedures

1. Collect

3. Analyze

4. Interpret

Results

Reducing the barrier to entry

Question

How can we reduce the barrier to entry (whether real orperceived)?

At least two ways:

I Speed up or automate edge-detection

I Develop alternatives to edge-detection

Results

Question

At least two ways:

Results

Question

At least two ways:

Results

Question

At least two ways:

Results

An observation (from a colleague)

./images/poster.jpgaNg@n@Na at”@N@

Results

Testing ground: Kaytetye

I Arandic language

I Spoken 300km north ofAlice Springs, NT

I Dozens of speakersremaining

Results

Kaytetye coronal inventory (phonemic)

dental alveolar retroflex palatal pre-palatal

oral stop t” t ú c jcnasal n” n ï ñ jñ

pre-stopped nasal t”n” tn úï cñjcñ

lateral l” l í L jL

Test question

Does production of alveolar compared to dental stops in Kaytetyeinvolve different motion of the tongue?

Results

Test question

Results

Test question

Results

DataSightedMeasured

Stimuli

I Target stops elicited in/#a a/ or /#a @/ contexts

I 8-12 repetitions of each item

I 7 female native speakers ofKaytetye (all multi-lingual tosome extent)

I Probe held by researcher

Results

DataSightedMeasured

Frames extracted

I 1 vocalic frame, from preceding vowel (a)

I 1 consonantal frame, at maximal constriction of targetconsonant

at”@N@

Results

DataSightedMeasured

Frames extracted

I 1 vocalic frame, from preceding vowel (a)

I 1 consonantal frame, at maximal constriction of targetconsonant

at”@N@ at”@N@

Results

DataSightedMeasured

Post-processing: sighted

at”@N@

1. Color consonantal frame (red)

2. Turn blacks in consonantal frame transparent

3. Combine frames

Results

DataSightedMeasured

at”@N@

3. Combine frames

Results

DataSightedMeasured

at”@N@

3. Combine frames

Results

DataSightedMeasured

Heights sighted

Naive coder instructed to “mentally trisect the white line in thecenter of the image” and rate

I +1 if red line is further from center than white

I 0 if red line is the same distance as the white from center

I -1 if red line is closer to center than white

Results

DataSightedMeasured

Heights sighted

+1 FRONT-1 MID0 BACK

Naive coder instructed to “mentally trisect the white line in thecenter of the image” and rate

I +1 if red line is further from center than white

I 0 if red line is the same distance as the white from center

I -1 if red line is closer to center than white

Results

DataSightedMeasured

Post-processing: measured

at”@N@

I Edge-detect both vocalic and consnoantal contours viaEdgeTrak (Li et al., 2005)

I Define three radial lines roughly approximating tonguetip/blade (FRONT), body (MID), and back (BACK)

Results

DataSightedMeasured

Post-processing: measured

at”@N@

I Edge-detect both vocalic and consnoantal contours viaEdgeTrak (Li et al., 2005)

I Define three radial lines roughly approximating tonguetip/blade (FRONT), body (MID), and back (BACK)

Results

DataSightedMeasured

Distances measured

-4 FRONT-21 MID21 BACK

I Distance along radial lines from vocalic (black) to consonantal(red) contours measured (pixels)

I Positive polarity if consonantal contour further from centerthan vocalic

Results

Measured vs. sighted resultsMeasured vs. sighted values

Results: measured

Test question

alveolar dental

●●

alveolar dental

Middle

alveolar dental

n.s. * p < 0.05 * p < 0.05

Results

Results: measured

Test question

Does production of alveolar compared to dental stops in Kaytetyeinvolve different motion of the tongue? Yes.

alveolar dental

●●

alveolar dental

Middle

alveolar dental

n.s. * p < 0.05 * p < 0.05

Results

Results: sighted

Test question

Yes, but only in MIDregion.

alveolar dental

Middle

alveolar dental

PlaceH

alveolar dental

n.s. * p < 0.05 n.s.

Results

Results: sighted

Test question

Does production of alveolar compared to dental stops in Kaytetyeinvolve different motion of the tongue? Yes, but only in MIDregion.

alveolar dental

Middle

alveolar dental

PlaceH

alveolar dental

n.s. * p < 0.05 n.s.

Results

Results vs. results

Measured Means Sighted Means

FRONT*

Alveolar -5.02 -0.25 11.04 -0.11 -0.12 0.99Dental -5.63 -12.79 8.35 0.13 -0.88 0.98

Results comparison

Sighted ratings capable of distinguishing between polarity, but arenot great at expressing variation in magnitude.

Results

Results vs. results

FRONT*

Alveolar -5.02 -0.25 11.04 -0.11 -0.12 0.99Dental -5.63 -12.79 8.35 0.13 -0.88 0.98

Results comparison

Sighted ratings capable of distinguishing between polarity

, but arenot great at expressing variation in magnitude.

Results

Results vs. results

FRONT*

Alveolar -5.02 -0.25 11.04 -0.11 -0.12 0.99Dental -5.63 -12.79 8.35 0.13 -0.88 0.98

Results comparison

Sighted ratings capable of distinguishing between polarity, but arenot great at expressing variation in magnitude.

Results

Values vs. values

●●

−1 0 1

Height Responses

●●

−1 0 1−

Height Responses

−1 < 0 < +1 −1 < 0 < +1 n.s.

Values direct comparison

Sighted rating is a reasonably good predictor for measureddistances.

Results

Values vs. values

●●

−1 0 1

Height Responses

●●

−1 0 1−

Height Responses

−1 < 0 < +1 −1 < 0 < +1 n.s.

Values direct comparison

Sighted rating is a reasonably good predictor for measureddistances.

Results

UsabilityViabilityAutomation

Summary

Suitable for

I First glances

I Small projects

I Visualization

I Teaching / demonstration?

Not suitable for

I Measuring distances automatically

I Comparisons involving small effects

I Projects with large amounts of data

Results

Summary

Suitable for

I First glances

I Small projects

I Visualization

I Teaching / demonstration?

Not suitable for

I Measuring distances automatically

I Comparisons involving small effects

I Projects with large amounts of data

Results

Typical procedures (revisited)

Time investment

Where can we save time?

1. Collect

2. Post-processI Extract relevant framesI Edge-detection

3. Analyze

4. Interpret

Results

Typical procedures (revisited)

Time investment

Where can we save time?

1. Collect

2. Post-processI Extract relevant framesI Edge-detection

3. Analyze

4. Interpret

Results

Qualitative vs. quantitative methods

Edge-detection or alternative: ?

I Measured (quantitative) –time-consuming

I Sighted (qualitative) – canbe automated?

Analysis: quantitative

I Sighted (qualitative) –human component

I Measured (quantitative) –can be largely automated

Automation

If qualitative methods are to be competitive, automation mustbe made possible.

Results

Automation

Results

Automation

Results

Automation

Results

Automation: first (naive) attempt

1. Increase contrast of both frames

2. Color all pixels above a white threshold (in one frame)

3. Make transparent all pixels below threshold (in same frame)

4. Overlay colored frame over uncolored frame

Results

Some reasonably successful...

at”@p@

Results

Some not so much

aú@p@: too much colored

Results

Some not so much

at@k@: too little colored

Results

Automation: second attempt

2. Split frame to be colored into blocks

3. For each block, if block contains “interesting information”

3.1 Color all pixels above a white threshold3.2 Make transparent all pixels below threshold

Results

Hmmm...

at”@p@

References

Li, M., Akgul, Y., and Kambhamettu, C. (2005). Edge Trak [Compuer Program]. Version 1.0.0.4. RetrievedOctober 3, 2008, from vims.cis.udel.edu/EdgeTrak/.

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