Lab Notebook of Kathryn Schuler

This is an index of all of the experiments I have run in graduate school. I keep a single summary file in the form of an iPython or R notebook for each experiment. Click on an experiment to view its summary. For more details on how I run experiments and document my work visit my experiment guide.

• QAXBR
  • Variable word frequency (Raggedyness)
  • Children (kid QAXBR)
  • Older adults (65+)
• Word Segmentation
• SRT
• Empirical Yang
• Incon Input
• Hierarchical Structure

---

---

Word Segmentation

In this line of work I ask whether learners can use a statistcal learning mechanism to segment words from fluent speech.

Replications of original experiments

Saffran et al. 1996; Newport & Aslin 2004

• 0140-babysaffran-replication-2afc
• 0141-babysaffran-replication-rating
• 0142-babyhebrew-replication-2afc
• 0143-babyhebrew-replication-rating

Word segmentation in patients with aphasia

Fama, Schuler, Turkeltaub & Newport

• 0060-babysaffran-nrh
• 0061-babysaffran-nrh-nback
• 0062-babysaffran-nrh-nback-winxp

---

SRT

In this line of work I use a novel SRT-task paradigm to observe the time-course of statistical learning.

Developing an SRT paradigm

Schuler, Newport, Howard & Howard

• 0010-srt-pilot
• 0011-asrt-keyboard-10
• 0012-asrt-keyboard-40
• 0020-asrt-touch-home
• 0021-asrt-touch-nh-square-10
• 0022-asrt-touch-nh-line-10
• 0023-asrt-touch-nh-line-40
• 0024-asrt-touch-2-random-20

Developing an SRT paradigm for children

Schuler, Newport & Aslin

• 0031-babysaffran-srt-tiny
• 0032-babysaffran-srt-petstore
• 0033-babysaffran-srt-tablet

Time-course of statistical learning, adjacent and non-adjacent dependencies

Schuler, Newport & Aslin

• 0030-babysaffran-srt
• 0034-babysaffran-srt-posttest
• 0040-babyhebrew-srt
• 0041-babyhebrew-srt-posttest
• 0042-babyhebrew-srt-bilingual

Time-course of learning in patients with aphasia

Schuler, Fama, Turkeltaub & Newport

• 0035-babysaffran-srt-patient

Time-course of learning of inconsistent variation

Schuler & Newport

• 0050-inconinput-SRT-random16
• 0051-inconinput-SRT-6733

---

---

Incon Input

In this line of work I ask how children acquire language variation.

Regularization of inconsistent input (5-day)

Austin, Furlong, Schuler & Newport

Developing a one-day paradigm

Schuler & Newport

• 0100-inconinput-3day-6733-4noun
• 0101-inconinput-3day-6733-english6noun
• 0102-inconinput-1day-pluralmorph-6733
• 0103-inconinput-1day-pluralmorph-6733-mturk

Sufficiency Principle in regularization

Schuler, Horowitz, Yang, & Newport

• 0500-inconinput-empiricalyang-33scatter
• 0500-inconinput-empiricalyang-33scatter

Regularization in adult learners

Schuler & Newport

• currently being designed

Acquisition of conditioned variation

Schuler, Furlong, & Newport

• 0401-experiment1
• 0402-experiment2
• 0403-experiment3

---

Hierarchical structure

In this line of work I ask how learners acquire hiearchically structured sytax and whether humans have a general cognitive assymetry bias for linearized or temporally presented hierarchies.

Hierachical trees

Handshuh, Schuler, Landau & Newport

• 0200-hierarchical-trees-pilot

Replicating Thompson & Newport in an SRT task

Schuler & Newport

• 0301-hierarchical-srt-thompsonnewport-correlatedcue
• 0302-hierarchical-srt-thompsonnewport-correlatedcue-posttest
• 0303-hierarchical-srt-thompsonnewport-nocue
• 0304-hierarchical-srt-thompsonnewport-nocue-alixlang

Learning bias for hierarchical structure

Schuler & Newport