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Maria Castro

CogNotes2.pptx

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Pattern Recognition

Langston, PSY 4040

Cognitive Psychology

Notes 2

What is this?

What's Out There?

We're going to explore how you know what it is that you're seeing, hearing, etc. Three steps:

Input: Get it into the system.

Identification: What is it?

Recognition: What does it mean?

Architecture

Recall our three boxes:

Sensory

Store

LTM

STM

Filter

Pattern

Recognition

Selection

Input

(Environment)

Response

Where We Start

The sensory system delivers information transduced from the environment, then we start.

Kind of a gray line…

Where We Start

Monocular cues to depth:

Linear perspective

Interposition

Relative size

Relative height

Texture gradient

Lighting/shading

Familiar size

Where We Start

Monocular cues to depth:

Linear perspective

Interposition

Relative size

Relative height

Texture gradient

Lighting/shading

Familiar size

Where We Start

Monocular cues to depth:

Linear perspective

Interposition

Relative size

Relative height

Texture gradient

Lighting/shading

Familiar size

Where We Start

Monocular cues to depth:

Linear perspective

Interposition

Relative size

Relative height

Texture gradient

Lighting/shading

Familiar size

Where We Start

Monocular cues to depth:

Linear perspective

Interposition

Relative size

Relative height

Texture gradient

Lighting/shading

Familiar size

Where We Start

Monocular cues to depth:

Linear perspective

Interposition

Relative size

Relative height

Texture gradient

Lighting/shading

Familiar size

Where We Start

Monocular cues to depth:

Linear perspective

Interposition

Relative size

Relative height

Texture gradient

Lighting/shading

Familiar size

Architecture

Recall our three boxes:

Sensory

Store

LTM

STM

Filter

Pattern

Recognition

Selection

Input

(Environment)

Response

Input (Sensory Store)

Generic questions:

Capacity?

Duration?

Code?

Forgetting?

Sensory Store

Present some information, get you to report it back:

Sperling (1960, p. 3)

Sensory Store

How do you report?

Whole report: Tell me everything you saw.

Partial report: Tell me some of it.

Why make a distinction? If you have a limited duration (and it makes sense for this to be short), it will fade before you can report it.

Look at the whole report data…

Sperling (1960, p. 5)

Whole report: Presentation for 50 ms, 5 observers, more information doesn't lead to more being reported, the amount stays around 4.5 items.

Sensory Store

Sperling (1960):

Partial report (tone tells you which row, high middle, or low).

Sperling (1960, p. 3)

Sperling (1960, p. 5)

Partial report: Presentation for 50 ms, 5 observers, they report about 75% of the available information.

Sensory Store

Sperling (1960):

The duration of the store is less than one second.

After the letters go away, present a tone. Vary it from -0.10 seconds to + 1.0 second. Return to whole report level around 0.25 seconds.

Sperling (1960, p. 9)

Sensory Store

Sperling (1960):

The code is relatively unprocessed information.

Forgetting is some form of decay.

Compare Sperling's (1960) results to your CogLab data…

Sensory Store

So what? Method.

People’s experience is that they can see more than they can report.

Sperling figured out how to verify that empirically.

He also figured out how to assess the duration of the information.

This problem of clever method uncovering private experience is key.

Sensory Store

So what? Method.

Let’s figure out how to do the experiment for an auditory sensory store…

Sensory Store

So what? Method.

Darwin, Turvey, and Crowder (1972):

Three lists played over headphones, left ear, right ear, middle.

Visual signal tells you what to report.

Capacity was smaller than visual (about 5 letters), duration was longer (about 2 seconds).

Sensory Store

So what? Method.

Massaro (1970):

Play a tone, wait, play a masking tone that interferes.

People report the original tone (high/low).

After the tone goes off, people can keep processing it to identify it. If the masking tone is too early, it disrupts this echoic memory.

Sensory Store

So what? Method.

Massaro (1970):

Massaro (1970, p. 413)

Sensory Store

So what? Method.

Massaro (1970):

If they weren’t using some persistent echoic memory after the tone, then it wouldn’t matter when you masked it.

Note that this kind of turns the task inside out.

The duration is also much shorter (1/4 second).

Sensory Store

So what? Input from the environment.

Life moves fast; you need a record of it before it gets away.

This lets you sample for later processing.

This is the start of the process.

Sensory Store

So what? Reading.

Eyetracking studies (Rayner & Sereno, 1994):

Three regions:

Foveal: High resolution, about 8 letters.

Parafoveal: Less acuity, some information available, about 12 (more?) letters.

Peripheral: Very low acuity, only gross information (e.g., ends of lines).

Sensory Store

So what? Reading.

Three parts:

Fixations: Gather information. Average 200-250 ms, range from 100-500 ms.

Saccades: Move to new fixation, about 8 characters, range from 1 to 15.

Regressions: Saccade to earlier part of the text, 10-15% of saccades.

Sensory Store

So what? Reading.

You have to hold information long enough to extract some of it, and then you have to get rid of it.

Think of the speed of fluent reading.

Architecture

Recall our three boxes:

Sensory

Store

LTM

STM

Filter

Pattern

Recognition

Selection

Input

(Environment)

Response

Identification

Bottom-up vs. top-down:

Representation

Input

Knowledge, etc.

Müller-Lyer

Top down fail?

Müller-Lyer

Top down fail?

Müller-Lyer

Top down fail?

Müller-Lyer

Top down fail?

Top Down

Three Models

Template model:

Identify by comparing to a copy of everything you’ve seen.

Possible support:

Instance theories.

Perceptual priming.

Three Models

Rotated word…

Three Models

Template model:

Identify by comparing to a copy of everything you’ve seen.

Problems:

Too much variability.

Problems in matching.

What defines a match?

Three Models

Template model:

Identify by comparing to a copy of everything you’ve seen.

Problems:

Too much variability.

Problems in matching.

What defines a match?

Multiple interpretations of the same stimulus.

Three Models

E.g.,

Three Models

Feature model:

Identify by breaking into features and analyzing those.

Good feature sets have these properties:

Critical (help you to tell things apart).

Same with changes in the input environment.

Unique pattern for every input.

Reasonably small number of features.

Three Models

Feature model:

Good things about feature models:

Fit nicely with information theory: With N features, you can classify 2N things.

1 feature -> 2 things.

2 features -> 4 things.

8 features -> 256.

20 features -> 1,048,576.

Work well with computers.

Three Models

Feature model:

Support:

Confusion matrices.

Cluster analyses (projector).

Face recognition.

Brain organization.

Three Models

Feature model:

Problems:

Hard to get the right set.

Can't ignore how features combine.

Three Models

Structure model:

Identify by grouping

Gestalt idea: The whole is greater than the sum of its parts. Grouping principles:

Proximity: Close = part of same group.

Similarity: Similar = part of same group.

Continuity: Group into continuous forms.

Three Models

Structure model:

Grouping principles:

Closure: Prefer closed figures.

Connectedness: Connected part of same group.

Closure

Three Models

Lanthier, Risko, Stolz, & Besner (2009; doi:10.3758/PBR.16.1.167):

In addition to features, information about how features combine is also important.

Delete information from midsegments:

Or vertices:

Lanthier et al. (2009, p. 68)

Three Models

Lanthier et al. (2009): The kind of information deleted mattered:

Lanthier et al. (2009, p. 68)

Three Models

Let's try a mini-experiment based on Biederman (1987).

Break into groups A and B.

You will write down the name of the object that you see.

All of the images that follow are from Biederman (1987, p. 135)

Group A get ready:

Group B get ready:

Answers…

Recoverable stimuli:

“The contours have been deleted in regions where they can be replaced through collinearity or smooth curvature” (p. 135).

Non-recoverable stimuli:

“The contours have been deleted at regions of concavity so that collinearity or smooth curvature of the segments bridges the concavity. In addition, vertices have been altered, for example, from Ys to Ls, and misleading symmetry and parallelism have been introduced” (p. 135).

Biederman (1987, p. 136)

Biederman (1987, p. 137)

Biederman (1987, p. 142)

Biederman (1987, p. 143)

Three Models

How can gestalt features help explain this?

Gestalt—Figure-Ground

Direct Perception

Gibson (e.g., 1950) proposed a theory of direct perception. A caricature:

Light is structured into an ambient optic array. Each point in this array carries potential information.

This information takes the form of affordances if a particular organism happens to be there to pick it up.

Information pick-up is direct.

Direct Perception

Perceiving affordances:

If I'm looking for a place to sit, sit-on-ableness will be perceived by me in objects that have that property. If I need something to throw, that will be afforded.

It's kind of like an automatic process in that there isn't conscious mediation. The affordance is just there.

Direct Perception

Evidence:

Warren (1984) had people look at various configurations of stairs to rate climbability.

People could accurately perceive climbability (based on a biomechanical model) from looking at the stairs.

102

Direct Perception

Evidence:

Warren (1984).

When short or tall people look at stairs, their climability judgements occur in different places.

Warren (1984, p. 689)

Direct Perception

Evidence:

Warren (1984).

When scaled to their bodies, the lines converge, and the values are almost identical and the same as predicted by the model.

Warren (1984, p. 689)

Direct Perception

Evidence:

Warren (1984) had people look at various configurations of stairs to rate climbability.

Also: There's an optimal configuration for minimum energy expenditure, people preferred stairs that fit this configuration; those preferences conformed to the model.

105

Direct Perception

Evidence:

People overestimate the slope of a hill when wearing a backpack full of rocks…

Proffitt (2006, p. 112)

106

Direct Perception

Proffitt (2006, p. 112)

107

Direct Perception

Note:

Verbal and visual subject to the illusion (effort is greater).

Haptic is not so much (that’s how you know what you’re actually seeing).

Solves a paradox: If doors look wider in some circumstances, how do you still walk through them correctly?

108

Recognition/Meaning

Meaning and identification appear to be separate.

What we'll do is look at language recognition (reading and listening) at several levels:

Letters

Orthography

Word superiority

Speech sounds

109

Recognition/Meaning

Letters: A number of features influence letter identification:

Serif vs. sans-serif (f vs. f)

Weight difference (e vs. e)

Bias

X-height

Spacing (proportional vs. non-proportional)

Proportions

110

Recognition/Meaning

Features can influence identification, as in this (admittedly not ideal) example:

111

Recognition/Meaning

Find the x:

N N Z N Z N Z N Z

Z N Z Z N Z Z N N

N N N Z N X N Z N

N N Z N Z N Z N Z

Z N Z Z N Z Z N N

112

Recognition/Meaning

Find the x:

O O P O P O P O P

P O P P O P P P O

O O P P O X P O P

O O P O P O P O P

P O P P O P P P O

113

Recognition/Meaning

Word recognition: Additional features:

Word envelope

Orthography: Rules for combining letters

Avoid doubling letters

To pronounce:

V C V

V C C V

V C

114

Recognition/Meaning

Word recognition:

Orthography

To correct a V C pattern, add a dummy e

Fin, fine, can, cane

To correct a V C V pattern, double

Runing, running

Orthography can help with:

Pronunciation: mab, mabing, mabe, mabbing

Letter expectations

115

Recognition/Meaning

An example of combining the additional features on word recognition: Word superiority effect.

Which should be identified better:

word

Look at CogLab data for word superiority…

116

Recognition/Meaning

Lanthier et al. (2009): When they put degraded letters into words:

Lanthier et al. (2009, p. 70)

117

Recognition/Meaning

A similar finding: Huey (1908) finds that words can be perceived at distances that are too far for the letters within the words to be perceived.

Note the paradox: How do you see the word without seeing the letters first?

118

Recognition/Meaning

Interactive activation: A possible explanation (McClelland & Rumelhart, 1981).

McClelland & Rumelhart (1981, p. 378)

119

Recognition/Meaning

McClelland & Rumelhart (1981, p. 380)

Click to edit Master text styles

Second level

Third level

Fourth level

Fifth level

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Recognition/Meaning

McClelland & Rumelhart (1981, p. 383)

Click to edit Master text styles

Second level

Third level

Fourth level

Fifth level

121

Recognition/Meaning

McClelland & Rumelhart (1981, p. 384)

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Recognition/Meaning

McClelland & Rumelhart (1981, p. 384)

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Recognition/Meaning

Putting it together:

Aoccdrnig to a rscheearch at an Elingsh uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoetnt tihng is taht frist and lsat ltteer is at the rghit pclae. The rset can be a toatl mses and you can sitll raed it wouthit porbelm. Tihs is bcuseae we do not raed ervey lteter by it slef but the wrod as a wlohe. ceehiro. (c.f., http://www.snopes.com/language/apocryph/cambridge.asp)

124

Recognition/Meaning

OK. Let's try unfamiliar text:

Tihs was onriglaily caeertd a lnog tmie ago in rposnese to an off-tpioc cmnoemt in a Sosaldht aciltre taht I cn'at fnid any mroe. Snice tehn, i'ts been pssaed aunord a lot. I hvae no ieda how or why, but mnay tosdnauhs of polpee cmoe hree ecah week to sblarmce wodrs.

125

Recognition/Meaning

First and last letters:

Gciarcdno ot esreacrh ta na Eilsngh evrsyuinti, ti eodsn't rettma ni hwta roedr teh relstte ni a rodw rae, eth nyol rpatotinm hitng si atht rftis nad satl tetrel si ta teh rihgt ecalp. Eht rets anc eb a toalt smse nda yuo nca lltis arde ti houtitw opmlrbe.

126

Recognition/Meaning

And the unfamiliar text:

Isht aws inialrylog redtcea a lnog miet goa ni opersesn ot na ffo-tiocp nmmotce ni a Lshsatod tacrlei ttah I ctan' fidn yan meor. Ncise nthe, 'tsi eenb daspes dornau a lto. I haev on edia ohw ro wyh, ubt nyma dostansuh fo eeplop coem heer hcae ekwe ot cresmbla rwods.

127

Recognition/Meaning

Clearly, the “first letters” claim has some validity. I would suggest that it gives two sources of constraint that still makes reading relatively easy:

Some of the letter order information is preserved in every word (word envelope).

Words of three letters or less are intact. Given the role of function words, that's a big deal.

128

Recognition/Meaning

Relate this to the interactive activation model. How might it account for your being able to read scrambled words? Or, why might it have a problem accounting for this?

129

Recognition/Meaning

What about these?

Tihs txet uess olny wdors taht are shrot.

Hilpapy aoutrhs sitll issnit on fwinollog dullfready oslotebe snellpig.

Psleae ntoe taht any uaeicipnntatd hmras to paiitprtancs or asrvede eetvns must be reroeptd to the oficfe of cnpioalmce.

Rsaerech tseihs taht cltionlecg cmlteope reday yuor hvae you sbuimt mnaes fisihend you dtaa are and to.

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Recognition/Meaning

What about these?

sbalermcd

saremlbcd

unirevisty

ustveniriy

ueiinrstvy

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Recognition/Meaning

What about these?

This list of words: painters, pertains, pantries, in loco parentis.

a. anhtrsicit, piacvrote, lsngoievns, chlrucanbe

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Recognition/Meaning

What about these?

This list of words: painters, pertains, pantries, in loco parentis.

a. anhtrsicit, piacvrote, lsngoievns, chlrucanbe

b. antichisrt, proaictve, lonivgness, ccrnuhable

133

Recognition/Meaning

What about this?

4|)V4|\|C3D l3e+$peA|< i$ whEn J00 +4lK L1K3 t|-|15. t0 u|\|d3r$+@|\|D jOo |\/|u5+ be lEET. 1f J00 4r3 NO+ lEe+ jOO C@|\|N0T 5p3A|< 0r ReAd +|-|I5.

134

Recognition/Meaning

What about speech?

Phone: Sound you can make (4,096)

896 used

about 100 account for almost all languages

Phoneme: Group of phones treated as one sound by a language

Morpheme: Smallest unit that conveys meaning

Listeme: An entry in your mental dictionary

135

Recognition/Meaning

What about speech?

Features matter. For example:

136

Recognition/Meaning

What about speech?

Two ways to describe speech:

Articulatory phonetics: Based on how you make a sound. A speech sound is:

Air + voicing + manner + place

Here's a link to a page with a clickable glossary: https://en.wikipedia.org/wiki/Place_of_articulation

137

Recognition/Meaning

English:

138

Recognition/Meaning

What about speech?

Two ways to describe speech:

Acoustic phonetics: Based on the actual, physical sound wave that is produced.

139

Recognition/Meaning

What about speech?

Acoustic phonetics uses the spectrogram.

Recognition/Meaning

What about speech? A couple of issues to provide an example:

Parallel transmission:

Recognition/Meaning

What about speech? A couple of issues to provide an example:

Context conditioned variation:

Recognition/Meaning

What about speech? An example of a top-down influence on speech perception:

McGurk effect: https://www.youtube.com/watch?v =aFPtc8BVdJk

Recognition/Meaning

Other context effects in recognition: Palmer (1975): Objects are recognized in an appropriate scene more than in an inappropriate context.

Palmer (1975, p. 519)

Recognition/Meaning

Palmer (1975, p. 521)

Meaning

A word means:

What it refers to (what it stands for)?

The image it calls up?

What else?

Meaning

A word means: A two-part model:

Propositions: Ideas

Models derived from them

E.g., the star is to the left of the circle

Grounding

Chinese-room problem: How are symbols grounded?

Embodied cognition?

Other ideas?

Dirty Disney

End of Pattern Recognition Show