1 / 7

English Theme 3 Sample presentation (4)

Date: 2007-05-15 Room: 8-309 Instructor: Mafuyu Kitahara Material: Balota D. A. (1994) “Visual word recognition” in M. A. Gernsbacher (ed.) Handbook of Psycholinguistics, pp. 303-358, San Diego: Academic Press. English Theme 3 Sample presentation (4). Interactive activation model. Structure

edith
Download Presentation

English Theme 3 Sample presentation (4)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Date: 2007-05-15 Room: 8-309 Instructor: Mafuyu Kitahara Material: Balota D. A. (1994) “Visual word recognition” in M. A. Gernsbacher (ed.) Handbook of Psycholinguistics, pp. 303-358, San Diego: Academic Press. English Theme 3 Sample presentation (4)

  2. Interactive activation model • Structure • Facilitate: • Inhibit: • Bottom-up • Within-level • Top-down

  3. How it works

  4. What about pseudoword? • MAVE similar to • MOVE, CAVE, MAKE, MADE, MATE… • MARK, MART, TAPE, CAKE, RAVE, PAVE… • No HIT on the real word • But enough activation from similar words • Better than nonword, e.g. MVEA

  5. Limitations of IA model • Bigram frequency (e.g. ee > oe) • Little effect in Reicher-paradigm • IA model explains successfully • Needs a large lexicon (over critical limit) • NEED(target) activates • NERD, NEAT, NEAR, NEAP, NEST…(needs more) • FEEL, PEEL, KEEP, LEEP, MEET… • Bigram freq has effect in Low-freq words? • Neighborhood  confusion • Still controversial…

  6. Other issues and beyond • Positional frequency • Fits well in IA model • LOGOGEN: frequency-ordered word lists • Similar words have effects • Then, what is “SIMILAR”?

  7. Schedule • 5/22: - p.315, before section B. • 5/29: - p.317, before “One of the more…” • 6/05: - p.319, before section C.

More Related