word_recognition

							Word Recognition


    Rauno Parrila
 University of Tromsø
 raunop@psyk.uit.no
            Contents

1. Definitions
2. Letter recognition
3. Sublexical units in word recognition
4. Lexical factors
5. Semantic factors
6. Language level factors
        Why word recognition?
   Word recognition literature cuts across
    several basic research areas in cognitive
    psychology
     verbal learning and memory
     memory access (via phonemes, morphemes,
      graphemes, semantics etc.)
     attention (automatic vs. controlled
      processing)
     pattern recognition (features vs. templates)
                 Definitions
   Phone
     elementary  speech sound or sound unit
      (acoustic unit)
   Phoneme
    a  group of speech sounds spelled with the same
      or equivalent letter and commonly regarded as
      the same sound. They may vary somewhat (be
      different phones) but do not differentiate
      between meanings.
   Allophones
     allphones not distinguished in a language as
      separate phonemes
Definitions cont.


   Homophones
       words that sound the same but are spelled
        differently
   Pseudohomophone
       nonword that sounds like a real word when
        pronounced
   Onset
     initial  consonant or consonant cluster in a
        syllable
   Rime
     everything    that follows in a syllable after onset
Definitions cont.


   Phonetics
     study   of raw sounds (phones)
   Phonology
     study   of sounds within a language (phonemes)
   Grapheme
    a letter or combination of letters that represent a
      phoneme (basic unit of written language)
   Morpheme
     unit   of structure that reflects meaning
Definitions cont.


   Morphology
     study   of words and word formation
   Semantics
     study   of meaning
   Pragmatics
     study   of language use
   Syntax
     study   of word order
  Word Recognition: The Task
1. Recognize input stimuli as letters (pattern
  matching)
2. Recognize combination of letters as a word
  (visually or via phononological recoding)
3. Retrieve the meaning from lexicon (lexical
  access)
4. Retrieve phonological representation (sound
  lexicon)
5. Assemble motor program for pronunciation
6. Execute pronunciation program
                          WRITTEN WORD
Naming
                            VISUAL
                           ANALYSIS
                            SYSTEM



                             VISUAL
                             INPUT
                            LEXICON

     SEMANTIC
      SYSTEM


                SPEECH                   GRAPHEME-
                OUTPUT                    PHONEME
                LEXICON                  CONVERSION




                PHONEME
                 LEVEL




                SPEECH
Lexical Decision
                        WRITTEN WORD


                          VISUAL
                         ANALYSIS
                          SYSTEM




               VISUAL                  GRAPHEME-
               INPUT                    PHONEME
              LEXICON                  CONVERSION




                          SEMANTIC
                           SYSTEM
                          (LEXICON)
       Visual Analysis System:
         Letter Recognition
 How do we recognize a group of lines and
  curves as letters?
 Two common explanations: Template
  matching and feature detection
                     Reisberg, , Chapter 2
           Template matching
 Stored representation in brain for every
  letter (every version of that letter)
 Costly: think of all the possible fonts,
  handwriting styles etc.
 Normalization before matching
 Perhaps enough space for letters but for all
  visual stimuli? Two different systems for
  letters and other visual stimuli?
              Feature detection
   analysis-by-synthesis
    1. Letter broken down to its constituent parts
    2. List of parts compared to patterns in memory
    3. Best matching pattern chosen
                    Feature demons    Cognitive demons
                    decode specific   “shout” when they
                       features       receive certain
                                      combinations of features




  Image Demon                                                    Decision demon
receives sensory                                                 “listens” for the
 input and sends                                                 loudest shout in
   signal further                                                pandemonium to
                                                                 identify input
A
          WRITTEN WORD


            VISUAL
           ANALYSIS
            SYSTEM




 VISUAL                  GRAPHEME-
 INPUT                    PHONEME
LEXICON                  CONVERSION




            SEMANTIC
             SYSTEM
            (LEXICON)
       Word recognition: Sounds
   Grapheme-phoneme correspondence
     print   to sound conversion by rules or analogies
   Spelling-sound regularity effect
        words with consistent spelling-sound relations are
         read aloud faster (by skilled readers) than irregular
         words
        no difference in lexical decision?

   Pseudohomophone effect
          Lexical decision speed slower with nonwords that
           sound like real words than with real words or with
           nonwords that do not sound like real words
   Homophone categorization
Word recognition: Groups of letters
 word superiority effect with words and
  orthographically regular (pronouncable)
  nonwords, but not with unpronouncable
  nonwords (Eysenck & Keane, p. 292)
 non-word legality effect (orthographic
  regularity effect)
        response time for nonwords following spelling
         patterns of real words longer than to nonwords that
         are not word-like (non-word legality effect)
        perhaps orthographic processing effect in general:
         words containing frequent letter bigrams or trigrams
         recognized faster than other words
   positional frequency effect
                HIGHER LEVEL INPUT
                                       McClelland & Rumelhart, 1981




                   WORD LEVEL




LETTER LEVEL                         PHONEME LEVEL




FEATURE LEVEL                          ACOUSTIC
                                     FEATURE LEVEL




VISUAL INPUT                         ACOUSTIC INPUT
    BAD       CAB




B   A     D    C    E
    Do other sublexical units help in
      recognizing printed words?
   Sublexical units bigger than phonemes and
    graphemes?
     onsets   and rimes
        onset: initial consonant or consonant cluster in a
         word or syllable
        rime: following vowel and consonants

        if words broken at onset-rime boundary, resulting
         letter clusters more easily recognized as belonging
         together than if broken at other points
        example:       FL OST ANK TR
                vs.     FLA ST NK TRO
         no role in visual word recognition?
 syllables:
 morphemes:
    root morpheme effect in lexical decision
    morphemic priming effect

       JUMP and JUMPED both prime JUMP
          WRITTEN WORD


            VISUAL
           ANALYSIS
            SYSTEM




 VISUAL                  GRAPHEME-
 INPUT                    PHONEME
LEXICON                  CONVERSION




            SEMANTIC
             SYSTEM
            (LEXICON)
           Lexical Level Variables
   Word frequency effect
        naming latency for high-frequency words shorter
         than for low-frequency words
        lexical decision time faster for high-frequency words
         than for low-frequency words
        shorter fixation durations for high-frequency words
         than for low-frequency words when reading a
         passage
   Word familiarity effect
        familiarity ratings usually based on subjective ratings
         (spoken word frequency) and frequency ratings to
         analysis of texts (written word frequency)
        independent familiarity effects in naming and lexical
         decision tasks (after frequency controlled)
   Lexical status effect
        response time to words faster than to nonwords in
         lexical decision tasks
        words named faster than nonwords (even pseudo-
         homophones)
     Why lexical access faster for high
      frequency and familiar words?
   activation explanation
     high-frequency   and familiar words will have
      higher resting level activations due to increased
      experience with them
   ordered search (list models)
     lexiconsearched serially with high-frequency
      and familiar words being searched before low-
      frequency and unfamiliar words
                 LION


Orthographic   Phonological    Semantic
access file    access file     access file
    LION           /l/i/o/n/
       lion
                  Semantic variables

   Neighbourhood effect (word similarity
    effect)
        nonwords with large ‘neighbourhood’ take longer to
         reject than nonwords with small neighbourhoods
        low frequency words with large ‘neighbourhood’ are
         recognized faster than low frequency words with
         small neighbourhoods
   Ambiguity (meaningfulness) effect
          more meanings, faster recognition
   Repetition priming
          familiar word encountered for the second or third
           time in a task is named and recognized faster than
           when it was encountered the first time
   Semantic (context) priming
        words appearing at the end of constraining sentence
         are recognized faster than otherwise
        eye fixations shorter (or skipped) when words
         highly compatible with context
        irrelevant context makes target words harder to
         recognize
        words appearing in isolation recognized and named
         faster if preceeded by a semantic associate
     difficult   to explain for the ordered search
      models
                   Summary
   Two routes to word recognition (lexicon):
    1. Direct visual access
        Lexical route, direct route, recognition by sight
         (sight-words), visual route
        Assumption is that some number of (common) words
         are recognized as visual units without access to
         sound based information
    2. Grapheme-phoneme conversion
        print-to-sound conversion, spelling to sound
         conversion, speech recoding, phonological recoding,
         phonological coding, deep phonological coding,
         phonetic recoding
        lexicon accessed through speech based code
      Which route is chosen?
 Differences between words (stimuli)
 Differences between individuals
 Differences between languages: Orthographic
  depth of the language
    1. shallow orthography: the phonemes of the
    spoken word are represented by the graphemes in
    a direct and unequivocal manner (isomorphism)
    2. deep orthography: spelling to sound relations
    (more) opaque (e.g., same letter may represent
    different sounds in different contexts, or different
    letters may represent the same sound in different
    contexts)
 Frost,   Katz, & Bentin (1987)
    Compared visual word recognition in Serbo-Croatian
     (shallow orthography), Hebrew (deep orthography),
     and English (medium)
    found that word frequency effect (high vs. low) and
     lexical status effect (words vs. nonwords) on naming
     speed depended on language; largest on Hebrew,
     smallest on Serbo-Croatian
    performance in lexical decision and naming tasks
     almost identical in Hebrew and clearly different for
     Serbo-Croatian
    semantic priming effected naming speed in Hebrew
     and English but not in Serbo-Croatian
                             WRITTEN WORD
Serbo-Croatian
(English)                      VISUAL
                              ANALYSIS
                               SYSTEM



                                VISUAL
                                INPUT
                               LEXICON

       SEMANTIC
        SYSTEM


                  SPEECH                    GRAPHEME-
                  OUTPUT                     PHONEME
                  LEXICON                   CONVERSION




                  PHONEME
                   LEVEL




                  SPEECH
                  (NAMING)
                                  WRITTEN WORD
Hebrew
(English)                           VISUAL
                                   ANALYSIS
                                    SYSTEM



                                     VISUAL
                                     INPUT
                                    LEXICON

            SEMANTIC
             SYSTEM


                       SPEECH                    GRAPHEME-
                       OUTPUT                     PHONEME
                       LEXICON                   CONVERSION




                       PHONEME
                        LEVEL




                       SPEECH
                       (NAMING)