Frost, R.

Monaghan, P.

English

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Simultaneous Segmentation and Generalisation from Nonadjacent Dependencies Rebecca Frost & Padraic Monaghan  Department of Psychology, Lancaster University  Contact:	  Dr	  Rebecca	  Frost,	  Department	  of	  Psychology,	  Lancaster	  University,	  r.frost1@lancaster.ac.uk	  	  	  	  	  Background Experiment 2: Sleep, Segmentation and Generalisation 	  Experiment 1: Segmentation & Generalisation 	  	  	  	  	  	  Conclusions References 1.  Peña,	  M.,	  Bona-,	  L.	  L.,	  Nespor,	  M.,	  &	  Mehler,	  J.	  (2002).	  Signal-­‐driven	  computaEons	  in	  speech	  processing.	  Science,	  298,	  604-­‐607.	  	  2.  Walker,	  M.	  P.,	  &	  SEckgold,	  R.	  (2010).	  Overnight	  alchemy:	  sleep-­‐dependent	  memory	  evoluEon.	  Nature	  Reviews	  Neuroscience,	  11,	  218	  	  3.  Gomez,	  R.	  L.,	  Bootzin,	  R.	  R.,	  Nadel,	  L.	  (2006).	  Naps	  promote	  abstracEon	  in	  language-­‐learning	  infants.	  Psychological	  Science,	  17,	  670-­‐674.	  This	  work	  was	  supported	  by	  the	  Economic	  and	  Social	  Research	  Council’s	  InternaIonal	  Centre	  for	  	  Language	  and	  CommunicaIve	  Development	  (LuCiD).	  	  SegmentaIon	  GeneralisaIon	  	  Figure	  2.	  Mean	  improvement	  scores	  for	  	  word	  vs.	  part-­‐word	  comparisons	  with	  95%	  CI	  	  §  54	  adults	  were	  randomly	  assigned	  to	  the	  SegmentaEon	  (N	  =	  18),	  Moved-­‐Syllable	  GeneralisaEon	  (N	  =	  18)	  and	  Novel-­‐Syllable	  GeneralisaEon	  (N	  =	  18)	  condiEons.	  	  The	  Language 	  	  §  ConEnuous	  stream	  of	  trisyllabic	  items.	  §  Items	  had	  an	  AxC	  structure,	  where	  A	  predicts	  exactly	  C.	  §  There	  were	  3	  A_C	  pairings:	  [pu-­‐ki],	  [be-­‐ga],	  [ta-­‐du]	  §  X	  was	  drawn	  from	  a	  varying	  set	  of	  intervening	  syllables. 	  	  	  Training	  §  A	  10.5-­‐minute-­‐long	  conEnuous	  speech	  stream.	  	  TesIng	  §  Two	  AlternaEve	  Forced	  Choice	  Task.	  	  Segmenta(on	  	  	  18	  word	  vs.	  part-­‐word	  comparisons.	  	  	  	  	  	  	  	  Part-­‐words	  occurred	  in	  the	  training	  speech,	  but	  straddled	  word	  boundaries.	  	  e.g.	  	  puraki	  beliga	  tafodu	  	  Moved-­‐Syllable	  Generalisa(on	  	  9	  part-­‐word	  vs.	  rule-­‐word	  comparisons.	  	  	  Rule-­‐words	  contained	  a	  trained	  A-­‐C	  dependency,	  but	  replaced	  the	  trained	  X	  items	  with	  an	  A	  or	  C	  from	  a	  different	  pairing.	  	  	  	  	  	  	  	  	  	  	  	  	  e.g.	  pugaki,	  bepuga	  	  §  Learners	  can	  simultaneously	  segment	  and	  generalise	  from	  nonadjacent	  	  	  	  	  	  	  	  	  	  dependencies.	  	  	  §  Changes	  to	  the	  learner,	  dependent	  on	  sleep,	  affected	  performance	  on	  these	  	  	  	  	  	  	  	  	  two	  tasks	  differenEally:	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  -­‐	  There	  is	  a	  longer-­‐las?ng	  benefit	  of	  sleep	  for	  segmenta?on,	  regardless	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  of	  whether	  that	  sleep	  is	  immediate	  or	  delayed.	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  -­‐	  There	  is	  a	  short	  term	  benefit	  of	  immediate	  sleep	  for	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  generalisa?on.	  	  	  	  	  A	  landmark	  study1	  tested	  learning	  from	  an	  arEficial	  language	  that	  disEnguished	  word-­‐idenEficaEon	  from	  learning	  grammaEcal	  dependencies	  between	  words.	  Although	  parEcipants	  could	  idenEfy	  words,	  they	  were	  unable	  to	  generalise	  the	  grammaEcal	  structure	  in	  the	  absence	  of	  addiEonal	  cues	  (e.g.	  pauses).	  But	  is	  this	  a	  true	  reflecEon	  of	  learners’	  abiliEes?	  	  In	  Experiment	  1,	  we	  assessed	  this	  by	  amending	  the	  test	  items	  used	  in	  previous	  studies	  to	  beker	  assess	  generalisaEon.	  	  Post-­‐learning	  sleep	  benefits	  a	  variety	  of	  tasks	  in	  language	  acquisiEon2.	  Advantages	  of	  sleep-­‐related	  consolidaEon	  have	  been	  shown	  for	  tasks	  involving	  abstracEon	  of	  structure	  and	  grammar	  acquisiEon3.	  But	  does	  sleep	  benefit	  different	  language	  learning	  tasks	  equally?	  In	  Experiment	  2,	  we	  extended	  this	  research	  by	  training	  parEcipants	  on	  the	  same	  language,	  and	  tesEng	  their	  word-­‐idenEficaEon	  (segmentaEon)	  and	  generalisaEon	  skills	  12-­‐	  and	  24-­‐	  hours	  later.	  	  A	  sleep-­‐related	  boost	  to	  segmentaEon	  would	  indicate	  that	  sleep	  benefits	  learning	  specific	  informaEon,	  whereas	  a	  sleep-­‐related	  boost	  to	  generalisaEon	  would	  indicate	  that	  sleep	  facilitates	  abstracEon	  of	  general	  informaEon	  relaEng	  to	  language	  structure.	  We	  hypothesise	  that	  sleep	  will	  benefit	  learning	  for	  both	  tasks.	  	  §  No	  significant	  effect	  of	  consolidaEon	  condiEon	  on	  either	  task.	  	  §  As	  in	  Peña	  et	  al.	  (2002),	  parEcipants	  significantly	  preferred	  words	  over	  part-­‐words,	  but	  showed	  no	  preference	  for	  rule-­‐words	  over	  part-­‐words.	  	  -­‐0.10	  -­‐0.05	  0.00	  0.05	  0.10	  0.15	  Test	  phase	  1	   Test	  phase	  2	  Improvement	  Score	  !0.10%!0.05%0.00%0.05%0.10%0.15%Test%phase%1% Test%phase%2%Improvement%Score%sleep!first%wake!first%Results: Delayed Testing	  § 	  	  No	  significant	  effect	  of	  tesEng	  	  	  	  	  Eme	  (p	  =	  .241)	  or	  consolidaEon	  	  	  	  	  	  	  	  	  condiEon	  (p	  =	  .643).	  	  § 	  	  But	  significant	  tesEng	  Eme	  by	  	  	  	  	  	  	  	  	  consolidaEon	  condiEon	  	  	  	  	  	  interacEon	  (p	  =	  .016),	  which	  	  	  	  	  	  indicated	  that	  performance	  was	  	  	  	  	  	  improved	  by	  immediate	  sleep.	  § 	  	  Significant	  main	  effect	  of	  tesEng	  	  	  	  	  	  	  Eme	  (p	  =	  .009).	  	  § 	  	  Significant	  main	  effect	  of	  	  	  	  	  	  consolidaEon	  condiEon,	  	  	  	  	  	  (p	  =	  044),	  with	  more	  improvement	  	  	  	  	  	  seen	  for	  the	  sleep-­‐first	  than	  the	  	  	  	  	  	  wake-­‐first	  group.	  § 	  	  No	  significant	  tesEng	  Eme	  by	  	  	  	  	  	  consolidaEon	  condiEon	  	  	  	  	  	  	  	  	  	  interacEon	  (p	  =.229);	  	  	  	  	  	  the	  sleep-­‐first	  group	  	  	  	  	  	  were	  consistently	  the	  most	  	  	  	  	  	  improved.	  !0.10%!0.05%0.00%0.05%0.10%0.15%Test%phase%1% Test%phase%2%Improvement%Score%sleep!first%wake!first%!0.10%!0.05%0.00%0.05%0.10%0.15%Test%phase%1% Test%phase%2%Improvement%Score%sleep!first%wake!first%Figure	  3.	  Mean	  	  improvement	  scores	  for	  	  rule-­‐word	  vs.	  part-­‐word	  comparisons	  with	  95%	  CI	  Results: Immediate Testing	  §  72	  adults	  were	  randomly	  assigned	  to	  the	  Sleep-­‐first	  (N	  =	  36)	  and	  Wake-­‐first	  (N	  =	  36)	  condiEons.	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  9am	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  9pm	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  9am	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  9pm	  Sleep-­‐first	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  training	  	  	  	  	  	  	  	  	  	  	  	  	  	  test1	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  test2	  Wake-­‐first	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  training	  	  	  	  	  	  	  	  	  	  	  	  	  test1	  	   	  	  	  	  	  	  	  test2	  §  Training:	  as	  before 	  	  §  TesIng:	  SegmentaEon	  and	  Moved-­‐Syllable	  GeneralisaEon	  (36	  test	  pairs)	  Novel-­‐Syllable	  Generalisa(on	  	  9	  part-­‐word	  vs.	  rule-­‐word	  comparisons.	  	  Rule-­‐words	  contained	  	  trained	  A-­‐C	  dependency,	  but	  replaced	  the	  trained	  X	  with	  a	  previously	  unseen	  item.	  	  	  	  	  	  	  	  	  e.g.	  puzowki,	  beveyga	  	  	  Results 0.00	  0.10	  0.20	  0.30	  0.40	  0.50	  0.60	  0.70	  0.80	  SegmentaEon	   Moved-­‐Syllable	  GeneralisaEon	  Novel-­‐Syllable	  GeneralisaEon	  Accuracy	  Figure	  1.	  Mean	  	  accuracy	  scores	  for	  each	  test	  condiEon	  §  SegmentaEon	  was	  significantly	  higher	  than	  chance	  (M	  =	  .719,	  p	  <	  .001).	  	  §  Moved-­‐syllable	  generalisaEon	  was	  at	  chance	  level	  (M	  =	  .487,	  p	  =	  .828).	  	  §  Novel-­‐syllable	  generalisaEon	  was	  significantly	  higher	  than	  chance	  (M	  =	  .693,	  p	  <	  .001).	  

Simultaneous segmentation and generalisation from nonadjacent dependencies

http://hdl.handle.net/11858/00-001M-0000-002E-73C8-1

Simultaneous segmentation and generalisation from nonadjacent dependencies

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