Word recognition Flashcards

1
Q

Womb learning who?

A

Moon et al. 2013

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2
Q

Womb learning what?

A

30 hour old babies were showed vowels in their mothers language and vowels in other languages

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2
Q

Womb learning what language was mothers tongue

A

Swedish or english

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2
Q

Womb learning findings

A

babies sucked their dummies harder when listening to a foreign language, shows they learn some speech in the womb

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2
Q

characteristics of what makes word recognition difficult

A

segmentation problem
invariance problem

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2
Q

segmentation problem

A

speech is a continuous stream of sound with no white space between words.

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3
Q

segmentation problem (2) solutions

A

possible word constraint (norris et al 1997)
Stress (cutler and butterfield 1992)

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4
Q

possible word constraint (norris et al 1997)

A

Fapple vs Wuffapple, any segmentation that results in impossible words is likely rejected (eg fapple)

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5
Q

Stress (cutler and butterfield 1992)

A

first syllable is typically stressed. Conduct ascents uphill hears as doctor sends the bill

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6
Q

The invarience problem

A

speech sounds are shaped by external factors

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7
Q

Co-atriculation

A

letters can be pronounced different such as e in mercedes or b in bill ball bull and bell.
“lean, bacon, lean bacon”

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8
Q

what causes coarticulation

A

dialect, speech rate and accent

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9
Q

context effects

A

knowledge about the contect in which a word occurs can help word recognition
semantics, syntax, etc.

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10
Q

Phenome restoration effect who?

A

warren and warren 1970

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11
Q

Phenome restoration effect what

A

audio on slide 10; was there a phenome missing “the state governers met with their respective legislatures convening in the capital city.”

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12
Q

Phenome restoration effect example (2)

A

It was found that the *eel was on the orange
It was found that the *eel was on the axle
It was found that the *eel was on the shoe
It was found that the *eel was on the table
peel, wheel, heel, meal

13
Q

theories of spoken word recognition

A

TRACE AND COHORT - most prominenet models

14
Q

TRACE who

A

McClelland and Elman 1986

15
Q

TRACE what?

A

3 layers - word units, phoneme units, feature units,

16
Q

Q: How does information flow in the TRACE model?

A

A: Information flows both bottom-up (from features to words) and top-down (from words to features).

17
Q

Q: What happens during word recognition in the TRACE model?

A

A: Words compete for recognition based on their similarity to the input, and activation levels change dynamically as speech unfolds.

18
Q

Q: How does context influence word recognition in the TRACE model?

A

A: Higher-level context can activate or suppress certain word candidates, influencing recognition.

19
Q

Q: How does the TRACE model handle continuous speech?

A

A: The model recognizes words in continuous speech without explicit word boundaries, using dynamic competition and activation processes.

20
Q

A criticism of TRACE

A

TRACE overestimates the influence of context
and predicts top-down effects where they do not
exist

21
Q

A criticism of trace cont.

A

Frauenfelder et al. (1990): TRACE predicts it’s hard to
detect /t/ in (French) nonword vocabutaire because
of the similar real word vocabulaire. Data did not
support prediction.

22
Q

Cohort model who?

A

Marlsen Wilson 1984

23
Q

Q: What is the “initial cohort” in the Cohort Model?

A

A: The initial cohort is the group of words activated based on the initial sounds of the spoken word.

24
Q

Q: How does the Cohort Model narrow down possible words?

A

A: As more speech input is processed, words that no longer match the input are eliminated from the cohort.

25
Q

Q: What is the “uniqueness point” in the Cohort Model?

A

A: The uniqueness point is the moment when only one word matches the incoming speech input.

26
Q

Q: How does context affect word recognition in the Cohort Model?

A

A: Context can influence cohort activation or elimination by providing semantic or syntactic cues.

27
Q

Q: How does the Cohort Model differ from the TRACE model in processing?

A

A: The Cohort Model uses a step-by-step narrowing of candidates (serial processing), while TRACE uses interactive, parallel processing.

28
Q

Q: How does the Cohort Model handle continuous speech?

A

A: It continuously updates the cohort as speech input unfolds, parsing overlapping signals in real time.

29
Q

Q: What factors influence word selection in the original Cohort Model?

A

A: Word selection is influenced by the auditory input and semantic/syntactic context

30
Q

Q: How can context affect word recognition in the original model?

A

A: Context can allow a word to be recognized before its uniqueness point by supporting a single candidate in the cohort.

31
Q

Q: What issue does the original model face with mispronunciations?

A

A: Words with mispronounced initial phonemes (e.g., “focabulaire” for “vocabulaire”) should not be recognized, but evidence shows they can still be.

32
Q

Q: How does the revised Cohort Model handle semantic context?

A

A: Semantic context no longer influences the early stages, making the model more bottom-up.

33
Q

Q: How are words managed in the revised model if they mismatch the input?

A

A: Words are not eliminated but have reduced activation, allowing revival if new evidence supports them.

34
Q

flashcard 6: Evidence for the Revised Model
Q: What evidence supports the revised model’s handling of mispronunciations?

A

A: Hearing “focabulaire” can still activate “vocabulaire” (Frauenfelder et al., 2001), showing mispronounced words are not fully excluded.

35
Q

Q: What did Zwitserlood (1989) find about semantic context in the revised model?

A

A: Semantic context does not influence which words remain in or leave the cohort of candidates.