language - speech perception

Question 1

components of the mental lexicon

Answer 1

syntax
phonological
semantics
orthographic

Question 2

challenges for lexical access (6)

Answer 2

• speech is a continuous stream
• Homonyms - Bank (£) versus Bank (river)
• homophones - Aisle vs Isle
• Co-articulation
• Different Accents
• Invariance problem - Problems of definition of acoustic properties - phonemes, syllables, words

Question 3

ambiguity in speech stream - word boundaries comedy example

Answer 3

Four candles or Fork handles

Question 4

disambiguating the speech stream - how word boundaries are distinguished (4)

Answer 4

Categorical perception

• Ability to distinguish between sounds on a continuum based on voice onset times

Voice Onset Time
* Vocal cord vibration – VVVVa vs FFa

Perceptual Learning

• Adjust categorical perception based on sounds we hear
• Seems to be hard-wired - babies and primates can do this

Top-Down Processing

• e.g. “The state governors met with their respective legislatures convening in the capital city.”
• cough disguising one sound in “legislatures” - top down processing allows us to recognise the word, and not identify which sound was blocked by the cough

Question 5

spreading activation

Answer 5

predictions of what may be coming up next via activation of items that are related to the acoustic input

e.g. apple –> appeal, apron, apollo, apply

Question 6

lexical characteristics - speed of lexical access (3)

Answer 6

word length –> long words = slower to process

neighbourhood density –> lots of neighbours = slower to process

frequency –> more frequently accessed words in lexicon = quicker access

Question 7

5 things lexical access is based on

Answer 7

• Bottom Up - Acoustic input
• Top down processing - disambiguating the speech stream
• Lexical characteristics
• Context
• Spreading activation that facilitates predictions

Question 8

3 options for mechanics of lexical access

Answer 8

1. gradually activate the word that matches the acoustic input
2. activate all words that start with the same sound as the acoustic input and gradually de-activate words that no longer match the sounds
3. gradually activate the word that matches the acoustic input more than other words

Question 9

mechanism of lexical access - 1. gradual activation of the word that matches the sound

Answer 9

different sounds can build up to a word

like phonics - breaks down a word

as the different sounds in the word are produced we gradually find the correct word

e.g. a –> ape –> april –> apricot

Question 10

mechanism of lexical access - 2. activate all words that sound like the start of the word, then gradually deactivate non-matches

Answer 10

as word is said, sounds are processed as the word is built up

e.g.
a –> a, ape, april, apricot
ape –> ape, april, apricot
april –> april, apricot
apricot –> apricot

Question 11

mechanism of lexical access - 3. gradually activate word that matches acoustic input more than other words

Answer 11

words with the sound in it - regardless of where it is in the word, not just at the start of a word

e.g.
a –> ape, pay, say, april, apricot
ape –> ape, april, apricot
april –> april, apricot
apricot –> apricot

Question 12

2 models of speech perception

Answer 12

Marslen-Wilson. (1987) –>The Cohort Model

access words in the lexicon via activation of all words sharing initial features and gradually de-activate words that stop matching the features (option 2)

Elman & McClelland. (1999) –> The TRACE model

features activate phonemes that activate words with a gradual increase in activation of words that match all features so that the word with the most activation wins (option 3)

Question 13

cohort model - lexical activation

Answer 13

activation of cohort that match the input
e.g. “ap-“ –> apricot, apex, apple, apart, april

then gradual deactivation of items that fail to match input
e.g. “apri-“ –> april, apricot

then find a uniqueness point - only one word activated
e.g. “apric-“ –> apricot

items that do not match the word onset are not activated (e.g. cot, prickly - match other word sounds within the word apricot)

Question 14

neighbourhood effects in cohort model

Answer 14

words that match the acoustic input compete for activation

e.g. apricot and aprikol

learning “aprikol” slows down recognition of the word “apricot” because of this

Question 15

frequency effects in cohort model

Answer 15

high frequency = high resting states = less activation required to recognise high frequency words

apricot would be recognised more quickly than aprikol (lower frequency word)

Question 16

evidence for cohort model - gating experiments

Answer 16

Warren & Marslen-Wilson 1987, 1988

participants are presented with fragments of words that gradually reveal the whole word and asked to guess what the word is after each presentation

example:
“john went to the zoo and saw a ca-“
= activate: cap, cat, caterpillar, camel, can, cannery, kangaroo

“…cam-“
= camel, can, cannery,

“…came-“
= camel

Grosjean (1980)
presented word “stretcher” - found same thing

Question 17

how gating experiments support cohort model

Answer 17

recognition of a word is a gradual process that starts from word onset and continues until the end of the word

candidate words that no longer fit the acoustic input are eliminated

Question 18

cohort model - structure

Answer 18

Marslen-Wilson & Warren (1994)

bottom up processing has priority

from speech input to lexical items (words)

via:

• facilitatory signals are sent to words that match the speech input
• inhibitory signals are sent to words that do not match the speech input

Question 19

issue with cohort model - bottom up processing

Answer 19

priority given to bottom-up processing

doesn’t account for phoneme restoration effect - missing sounds are perceived by listeners

Question 20

cohort model - 3 stages to word recognition

Answer 20

access

• acoustic-phonetic information is mapped onto lexical items

selection

• candidate words that mismatch the acoustic input are de-selected

integration

• semantic and syntactic properties of the word are integrated and checked against the sentence

Question 21

cohort model - impact of context

Answer 21

sentence context does not influence the process of lexical access

lexical selection is based on activation of phonology and semantic information

integration is affected by sentence context ( only a very little bit )

Question 22

context processing - priming paradigm

Answer 22

priming paradigm:

prime = doctor
target = nurse

semantically related words - spreading activation allows “nurse” to become active when “doctor” is presented

whereas if prime is “sheep”, “nurse” would not be activated

Question 23

cross modal priming

Answer 23

Zwisterlood (1989)

prime = auditory
target = visual

can have related/unrelated prime-target pairs
e.g. captain –> ship, or captain –> wicket

faster reaction time for related than unrelated pairs

priming effect = difference between related and unrelated reaction times

also use a word fragment as a prime (ambiguous):
related = capt- –> ship
related = capt- –> slave
unrelated = capt- –> wicket
(capt- could be captain or captive)
priming effect seen here too

Question 24

cross modal priming - with context

Answer 24

could have a neutral priming sentence:
“The men stood around for a while and watched their capt-“

or with context (bias):
“The men had spent many years serving under their capt-“

priming effect seen in both neutral and biased priming sentence with word fragments - ship and slave both activated with “capt-“ fragment

not seen on biased sentence with full word “captain” - only ship activated, not slave

items that match acoustic input but do not match sentence context are activated

items that match acoustic input but do not match sentence context are deactivated once the word is selected

supports cohort model - about acoustic input and how words in cohort are deactivated once word is selected (only when whole word is shown)

Question 25

revised cohort model

Answer 25

Marslen-Wilson & Warren, 1994 Context influences selection/integration of word into sentence The word with semantic activation that fits the context of the sentence will be integrated into the sentence. The men had served for many years under their /capt/ Semantic representation of captain is a better fit to the sentence than the semantic representation of captive and helps to single out ‘captain’ as the appropriate word

Question 26

debate over context - zwisterlood vs cohort model

Answer 26

Zwitserlood - context effects were observed before the acoustic input provided enough information to disambiguate the prime word. The Cohort model predicts that context only affects integration of the word into the sentence Zwitserlood argued that context affects word selection

Question 27

summary of cohort model

Answer 27

* Speech perception is based on matching acoustic input to stored representations of words in the lexicon * Words are recognised via a competitive process that activates a word ‘cohort’ * Cohort candidates do not actively engage with each other * Words are identified when they reach their uniqueness point * Cohort candidates that do not match acoustic input are eliminated * Context does not constrain activation of initial cohorts but allows for rapid elimination of candidates that do not match sentence context

Question 28

TRACE model

Answer 28

McClelland & Elman, 1986 words are recognized “incrementally by slowly ramping up the activation of the correct units at the phoneme and word levels”

Question 29

lexical activation in the TRACE model

Answer 29

"ap" --> apricot, tape, apex, shape, apart, apple, april "apri" --> apricot, april, apple "apric" --> apricot these words are just activated more than others - not deactivation of other words (other words aren't deactivated as such, they weren't totally activated in the first place)

Question 30

lexical competitive inhibition

Answer 30

as more sounds are given, other words are activated e.g. "apri" --> apricot, april apric --> apricot, prickly

Question 31

TRACE model - connectionist principles

Answer 31

Processing units (nodes) correspond to mental representations of: * features (voicing, manner of production), * phonemes * words

Question 32

TRACE model structure

Answer 32

bottom up and top down bottom up: * each level is connected via facilitatory connections * activation spreads up from features to lexical items * features (acoustic-phonetic patterns) --> phonemes --> lexical items top down: * faciliatory connections between levels also travel down from the lexical level to the phoneme level and the feature level * lexical items --> phonemes --> features connections between nodes within each level are inhibitory e.g. /v/ vs /b/ vs /d/ at the phoneme level are distinguished between

Question 33

TRACE model - process example of word "van"

Answer 33

trying to perceive "van" - bottom up processing FEATURE = phoneme activation - of /v/ /b/ /d/ (could be any of these PHONEMES = then match to /v/ and inhibit the other potential sounds that no longer match LEXICAL ITEM = remaining phonemes would be activated and in turn activate words that matched the input (vat, vamp, van, ban, can, pan) then van inhibits these other options top down can also occur - reinforces activation of nodes selected in previous levels

Question 34

TRACE - radical activation model

Answer 34

any consistency between input and representation may result in some degree of activation * nodes influence each other according to their activation levels & strengths of connections * activation develops as a pattern of excitation from facilitation and inhibition * candidate words are activated based on the pattern of activation * bottom up and top down processes: * bottom up - Activation from feature to word level * top down – Activation from word to feature level

Question 35

evidence for TRACE - activation of words in lexicon

Answer 35

Allopenna et al (1998) eye tracking study visual world paradigm found words rhyme competitors (overlapping phonology, not same start as the speech input) are activated in speech perception method: * grid containing images of rhyming items, e.g. beaker, beetle, speaker, pram - and shapes * task = click on the "beaker" and place it under the "triangle" * monitored eye movements whilst they complete the task * if words related to beaker are active in the lexicon participants will look towards those items predictions: * if TRACE = look at the beaker, beetle, and speaker (rhyme and onset) * if cohort = look at beaker and beetle, not speaker (onset only) results: * look at beaker and beetle in first 400ms * then beetle begins to drop * also look at speaker between 400-600ms after word heard - as beetle drops discussion: * words that rhyme with sounds in any part of a word may become activated * the initial Cohort of words activated in response to the speech stream is not limited to words with the same onset

Question 36

top-down processing of speech perception - supporting evidence

Answer 36

Mirman et al (2008) faciliatory links between words and phonemes should result in more accurate detection of phonemes in words compared to non-words method: participants asked to detect a /t/ or /k/ in words (e.g., highten) and non words (e.g., vinten) should find it easier to identify the /t/ in highten compared to vinten results: faster identification of /t/ and /k/ in words than non-words - participants expect them to be there demonstrates top-down

Question 37

top-down processing of speech perception - contradicting evidence (2)

Answer 37

phoneme detection --> participants can accurately detect phonemes in non-words that were word like e.g., /t/ in vocabutary participants failed to complete ambiguous phonemes with a phoneme that would create a word unless stimuli were degraded e.g., identifying ‘sh’ as the final phoneme for the ‘fiss’

Question 38

TRACE vs cohort model

Answer 38

top-down: * TRACE emphasises top down processing * Cohort model minimises the impact of top down processing lexical access/activation: * TRACE model accommodates the activate of rhyming competitors * Cohort model predicts that lexical access is biased towards activation of words with shared onsets context: * TRACE model does not provide an account of how context might affect speech perception * the evidence also suggests that there is a tendency to activate words that start with the same sounds * cohort model only mentions context at the very end and only a tiny bit -

Question 39

speech perception - which model is better according to Jusczyk and Luce (2002)

Answer 39

There is “now strong consensus in the field that activation-competition models of spoken word recognition—much in the spirit of the original Cohort theory— best capture the fundamental principles of spoken word recognition”