computational models of speech perception

Question 1

challenges for lexical access

Answer 1

• speech is a continuous stream
• homonyms
  –> spelt and said the same but different meanings
• homophones
  –> spelt differently, said the same, different meaning
• co-articulation
• different Accents
• invariance problem
  –> problems of definition of acoustic properties (e.g. phonemes, syllables, words)
• ambiguity in word boundaries
  –> e.g. four candles vs fork handles

Question 2

ways to disambiguate the speech stream

Answer 2

• categorical perception
• voice onset time
• perceptual learning
• top down processing

Question 3

categorical perception

Answer 3

ability to distinguish between sounds on a continuum based on voice onset times

Question 4

voice onset time

Answer 4

vocal cord vibration
–> VVVVa vs FFa

Question 5

perceptual learning

Answer 5

• adjust categorical perception based on sounds we hear
• seems to be hard wired
  –> babies and primates can do this

Question 6

top down processing

Answer 6

• 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 7

spreading activation

Answer 7

• facilitates predictions of what may be coming up next via activation of items that are related to the acoustic input
• when hearing ‘apple’
  –> appeal
  –> apron
  –> appear
• all may be activated in the lexicon

Question 8

what lexical characteristics affect the speed of lexical access?

Answer 8

• word length
  –> long words are slower to process
• neighbourhood density
  –> words with lots of neighbours are processed more slowly
• frequency
  –> more frequently a word is accessed in the lexicon, the quicker you can access it

Question 9

lexical access is based on?

Answer 9

• bottom Up (acoustic input)
• top down processing (disambiguating the speech stream)
• lexical characteristics
• context
• spreading activation that facilitates predictions

Question 10

mechanics of lexical access (3 options)

Answer 10

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 11

option 1 for lexical access

Answer 11

• e.g. word = apricot
  –> we break up each sound
  –> ay - pri - cot

Question 12

option 2 for lexical access

Answer 12

• e.g. word = apricot
• as soon as we hear ‘ay’ we might think of:
  –> april
  –> ape
  –> apricot
• as we continue to hear the word we de-activate words that no longer match
  –> after ay - pri is heard ‘ape’ is de-activated
  –> after ay - pri - cot is heard ‘april’ is de-activated

Question 13

option 3 for lexical access

Answer 13

• e.g. word = apricot
• when we hear ‘ay’
• we might activate:
  –> ape
  –> apricot
  –> april
  –> say
  –> pay
• as we hear more of the word, we activate the word that matches the word more than others
  –> e.g. apricot more than say

Question 14

2 models of speech comprehension

Answer 14

1. The Cohort Model
   –> Marslen-Wilson (1987)
   –> predicts that we 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)
2. The Trace Model
   –> Elman & McClelland (1999)
   –> predicts that 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 15

The Cohort Model

Answer 15

• we activate words in the mental lexicon (the cohort) that match the input
  –> e.g. the ‘ay’ in apricot can activate apple, apart, apricot, apex, april, ape
• we then gradually de-activate items that fail to match the input
• we reach a uniqueness point (we now know the word - only one word)
• items that do not match the onset of the word (‘ay’ in apricot) are not activated

Question 16

neighbourhood effects in The Cohort Model

Answer 16

• words that match the acoustic input compete for activation
  –> neighbours compete with each other for recognition
• learning the word ‘aprikol’ will slow down the recognition of the word apricot

Question 17

frequency effects in The Cohort Model

Answer 17

• words with high frequency have high resting states
  –> less activation required to recognise high frequency words
  –> e.g. apricot would be recognised more quickly (ms) than a low frequency word (aprikol)

Question 18

evidence of The Cohort Model

Answer 18

• Gating experiments
  –> Ps are presented with fragments of words that gradually reveal the whole word and asked to guess what the word is after each presentation
  –> e.g. john went to the zoo and saw a ‘ca…’
  –> cap
  –> cat
  –> kangaroo
• gradually more of ‘ca’ is told to help guess the word

Question 19

early findings of Gating Paradigm (Grosjean, 1980)

Answer 19

• presented the word stretcher using the paradigm

Question 20

what do Gating experiments suggest?

Answer 20

• 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 21

architecture of The Cohort Model

Answer 21

• facilitatory signals are sent to words that match the speech input
• inhibitory signals are sent to words that do not match the speech input
• bottom-up processing has priority
  –> but what about when we can activate a word with missing sounds? (e.g. the legislature cough example)

Question 22

what is the phoneme restoration effect?

Answer 22

• a sound is missing
• part of the word is missing or blocked by noise
• BUT we can still process the full word
• this can’t be bottom up processing
  –> top-down processing has to be involved

Question 23

3 stages to word recognition in The Cohort Model

Answer 23

1. access
   –> acoustic-phonetic information is mapped onto lexical items
2. selection
   –> candidate words that mismatch the acoustic input are de-selected
3. integration
   –> semantic and syntactic properties of the word are integrated and checked against the sentence

Question 24

the impact of context on The Cohort Model

Answer 24

• 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

Question 25

the priming paradigm

Answer 25

• lexical decision task
• asked to determine if a presented word is a word or non-word
• a prime can be presented before the target word
• if the prime is semantically similar to the target word, we are quicker to determine the word is a word
• prime is rapid (we don’t even see the prime)
• related words = faster response

Question 26

cross modal priming (Zwitserlood, 1989)

Answer 26

• prime word is auditory
• target word is visual
• had related/unrelated words and did the lexical decision / priming task
• found that reaction time was faster for related words than unrelated words

Question 27

cross modal priming (Zwitserlood, 1989) - word fragments

Answer 27

• given a word fragment
  –> e.g. ‘capt’
• then given slave, ship and wicket as a prime
• BOTH slave and ship should be activated in the lexicon
• wicket should not
• would predict to see faster response to slave and ship compared to wicket

Question 28

cross modal priming (Zwitserlood, 1989) - neutral vs bias

Answer 28

• neutral:
  –> sentence where ‘captain’ and ‘captive’ would be fine
• bias:
  –> sentence like ‘men had spent many years serving under their capt’ lead to activation of captain and not captive
  –> thus we would expect to see priming effect for ONLY the ship prime and NOT slave or wicket
  –> BUT STILL FOUND PRIMING FOR BOTH SLAVE AND SHIP

Question 29

cross modal priming (Zwitserlood, 1989) - complete sentence

Answer 29

• bias sentences were then completed
• “The men had spent many years serving under their captain”
• NOW priming was ONLY found for ship

Question 30

1978-1997 Cohort Model predictions

Answer 30

• 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

Question 31

revised Cohort Model (1994)

Answer 31

• 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
• semantic representation of captain is a better fit to the sentence (men served under their___) than the semantic representation of captive and helps to single out ‘captain’ as the appropriate word

Question 32

summarise The Cohort Model

Answer 32

• 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 33

the TRACE model

Answer 33

• in TRACE words are recognized “incrementally by slowly ramping up the activation of the correct units at the phoneme and word levels”
• gradual activation of item that matches the input

Question 34

competition in the TRACE model

Answer 34

• lexical competitive inhibition
  –> inhibitory signals are sent to words that no longer match
  –> more activation/signals sent to the word that does match

Question 35

architecture of TRACE model

Answer 35

• implemented computational model based on connectionist principles
• processing units (nodes) correspond to mental representations of:
  1. features (voicing, manner of production)
  2. phonemes
  3. words

Question 36

architecture of TRACE model - continued

Answer 36

• bottom-up processing
  –> each level is connected via faciliatory connections
• activation spreads up from features to lexical items
• top down processing
  –> facilitatory connections between levels also travel down from the lexical level to the phoneme level and the feature level
• connections between nodes within each level are inhibitory

Question 37

differences between TRACE model and Cohort model

Answer 37

• bottom-up and top-down processing in trace model
• top down processing reinforces activation of the nodes selected in previous levels
  –> this accounts for the phoneme restoration effect
  –> Cohort does not

Question 38

is the TRACE model a radical activation model?

Answer 38

• yes
• any consistency between input and representation may result in some degree of activation

Question 39

summarise the TRACE model

Answer 39

• 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 40

Allopenna et al (1998)

Answer 40

• using an eye tracking study demonstrated that words with overlapping phonology, that do not start with the same onset as the speech input (rhyme competitors), are activated in speech perception
  –> i.e. endings are similar

Question 41

Allopenna et al (1998) - method

Answer 41

• participants are presented with a grid that contains images of items such as this grid with a beaker, a beetle a speaker and a pram
• participants asked to click on the beaker and place it under the triangle
• participants eye movements are monitored whilst they complete the task
• if words related to beaker are active in the lexicon participants will look towards those items

Question 42

cohort model predictions for Allopenna et al (1998)

Answer 42

• no activation for pram or speaker
• should have activation for beetle and beaker
  –> they start with the same sound
• should look at beaker and beetle

Question 43

TRACE model predictions for Allopenna et al (1998)

Answer 43

• should look at beaker and beetle and speaker
• NOT pram
• 3 words are all similar in some way and so should be looked at

Question 44

Allopenna et al (1998)- results

Answer 44

• participants looked at the Beaker the Beetle and the Speaker
  –> participants looked at the Beaker and the Beetle in the first 400ms after the word was heard
  –> participants also looked at the Speaker between 400-600ms after the word was heard
  –> slower but it’s there (in line with TRACE model)

Question 45

conclusions from Allopenna et al (1998)

Answer 45

• the evidence from Allopenna et al. (1998) and others suggests that 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 46

top down processing

Answer 46

• faciliatory links between words and phonemes should result in more accurate detection of phonemes in words compared to non-words
• participants asked to detect a /t/ or /k/ in words (e.g., heighten) and non words (e.g., vinten) should find it easier to identify the /t/ in heighten compared to vinten

Question 47

Mirman et al (2008) results - top down processing

Answer 47

• faster identification of /t/ and /k/ in real words
• demonstrates the effect of top-down processing

Question 48

is top down processing superior?

Answer 48

• participants were able to accurately detect phonemes in non-words that were word like (Fraudenfelder et al. 1990 - e.g. /t/ in vocabutary)
• participants failed to complete ambiguous phonemes with a phoneme that would create a word unless stimuli were degraded (McQueen, 1991 - e.g. identifying ‘sh’ as the final phoneme for the ‘fiss’)

Question 49

TRACE vs Cohort

Answer 49

• the TRACE model emphasises top down processing
  -the Cohort model minimises the impact of top down processing
• the Cohort model predicts that lexical access is biased towards activation of words with shared onsets
• the TRACE model accommodates the activate of rhyming competitors
• the 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

Question 50

conclusions

Answer 50

• models of speech perception agree that we access words in the lexicon via activation of lexical representations
• there is also agreement that activation is based on processes that involve facilitatory signals and competition
• however the models take different routes to comprehension