This is our wonderfully ambitious schedule.
We'll attempt to keep with it, but it is subject to modification.
| Date | Topic | Readings (* = to be read by this class. All others are reference readings) |
Notices & Reading Questions |
| 9/24/15 |
Admin, Selection of articles, and Intro to Lang Acq [Lisa] |
(1) Jackendoff 1994: 3-34 [Ch 1, 2, 3] (2) O'Grady 2005: 164-175 (3) Goodluck 2010 - nativist perspective on language acquisition (4) O'Grady 2012 - review of alternate hypotheses to UG (5) Yang 2010 Ms, Yang 2011 - Zipfian distributions in language (6) Kuhl 2010 TED talk: first 10 minutes |
Introductory message board discussion points due |
| 9/29/15 |
Mechanism & Methods [Stephen] |
* (1) Marr 1982:
Ch.1 (only pp. 24-29 [pp.12-14 of
pdf]) * (2) Pearl & Goldwater (forthcoming) Marr's Levels (A1) Bechtel & Shagrir 2015: contributions of the three levels (A2) Griffiths et al. 2015: between computational and algorithmic (A3) Cooper & Peebles 2015: integrated cognitive architectures that use the three levels (A4) Love 2015: algorithmic level (A5) French & Thomas 2015: emergent structures and Marr’s levels Mechanisms (B1) Romberg & Saffran 2010: overview of infant statistical learning abilities (B2) Aslin & Newport 2012: overview of infant & adult statistical learning abilities (B3) Denison et al. 2013: probabilistic reasoning in infants (B4) Roseberry et al. 2011: domain-general statistical learning in infants (B5) Davis et al. 2011: probability matching in 10-month-olds (B6) Gweon et al. 2010: infant sensitivity to the sampling environment (B6) Dewar & Xu 2010: infant formation of overhypotheses (B7) Lany & Gomez 2012: probabilistic learning (when perfect cues are not as helpful) Experimental Methods (C1) Kidd et al. 2010, Kidd et al. 2012: infant looking time preferences -- what controls it (C2) Ambridge & Rowland 2013: experimental methods in language acquisition Computational Methods (D1) Clark & Sakas 2011: short overview of the utility of comp modeling (D2) Pearl 2010: how & when to use comp modeling (D3) Frank 2012 Ms.: overview of comp modeling in language acquisition (D4) Bonawitz et al. 2011: simple sequential algorithm for approximating Bayesian inference (D5) Perfors et al. 2011: Bayesian tutorial for cognitive development (D6) Gopnik & Tenenbaum 2007: overview of Bayesian inference & cognitive development + Gopnik & Schultz 2007: humorous exchange about Bayes nets and cog dev (D7) Kemp, Perfors, & Tenenbaum 2007: hierachical Bayesian overview (D8) Perfors 2012: Thoughts on how to use Bayesian modeling (D9) Orbanz & Teh 2010: reference for details of non-parametric Bayesian models (D10) Tenenbaum et al. 2011: Bayesian inference for cognition (D11) Griffiths et al. 2012: Neural nets vs Bayes (D12) Abbott et al. 2012: Bayesian inference approximation (D13) Jones & Love 2011: Bayesian fundamentalism or enlightenment + Marcus & Davis 2013 criticism (D14) Frank 2013: utility of Bayesian models |
Message board discussion points due |
| 10/1/15 |
Speech Perception [Georgina] |
* (1) Feldman
et al. 2013 Background (A1) Werker 1995: background on phoneme perception (A2) Swingley 2009: general overview, plus a section on the sounds of words (A3) The Linguistic Genius of Babies (up through 10:15 is a good general overview) (A4) Casserly & Pisoni 2010: general overview of speech perception & production Experimental (B1) Dietrich, Swingley, & Werker 2007: 18-month-old sound discrimination when in word context (B2) Yoshida et al. 2010: 10-month-old infant phoneme discrimination abilities (B3) Maye et al. 2002: infant sensitivity to bimodal distributions (B4) Maye et al. 2008: update on infant distributional abilities (bimodal facilitation for phonetic learning) (B5) Monahan & Idsardi 2010: biological plausibility of extracting phonetically relevant info from acoustic data (B6) Feldman et al. 2011, 2013: human learner sensitivity to word context of a sound (B7) Thiessen 2011: expt evidence that infants use word context when distinguishing sounds (B8) Thiessen & Pavlik 2013: why minimal pairs really aren't helpful to children (holistic representation helps distinguish prefixes) Computational (C1) Feldman, Griffiths, & Morgan 2009: shorter version of Feldman et al. 2013 (C2) Vallabha et al. 2007: identifying vowels from acoustic data (C3) Elsner et al. 2012: learning phon categories and words from child-directed speech (C4) Adriaans & Swingley 2012: useful cues to phonetic categories (C5) Martin et al. 2013: learning phonemes with proto-lexicons (simultaneous problem solving) (C6) Dillon et al. 2013: joint learning of phonetic categories and phonemes |
Message board discussion points due |
| 10/6/15 |
Speech Segmentation I
[Bailey] |
* (1) Blanchard
et al. 2010: cog plausible inference with
phonotactic constraints Background (A1) Sondregger 2008 Ms: overview of infant word segmentation behavior & strategies Experimental (B1) Saffran, Aslin, & Newport 1996: infant probability tracking (B2) Gomez & Gerken 2000: artificial language expts (B3) Finn & Hudson Kam 2008: issues with adults in artificial language expts (B4) Onnis et al. 2005: issues with adults in artificial language expts (B5) Johnson & Tyler 2010: issues with infant sensitivity to trans prob (B6) Lew-Williams et al. 2011: utility of isolated words for word seg (B7) Mersad & Nazzi 2012: utility of familiar words in word seg (B8) Willits et al. 2009: morpheme tracking (B9) Kurumada et al. 2013: Zipfian distribution, using context, implementing chunking Computational (C1) Gambell & Yang 2006 Ms, Lignos 2011, Lignos 2012: algebraic learning + stress + probabilistic memory (C2) Swingley 2005: using mutual information over syllables (C3) Jarosz & Johnson 2013: comp analysis of distributional cues utility (useful when combined, but not separately) (C4) Ketrez 2014: vowel harmony as statistical word seg cue (C5) Daland & Pierrehumbert 2011: model based on diphones |
Message board discussion points due |
| 10/8/15 |
Speech Segmentation II [Stephen] |
* (1) Phillips
& Pearl 2015 Experimental (A1) Frank et al. 2010: Bayesian model matching human word seg performance Computational (B1) Phillips & Pearl 2012: constrained Bayesian word seg over syllables (shorter version of Phillips & Pearl 2015) (B2) Goldwater et al. 2009: ideal learner Bayesian model (B3) Johnson & Goldwater 2009: ideal learner Bayesian model (B4) Pearl et al. 2010, 2011: more cognitively plausible algorithms (B5) McInnes & Goldwater 2011: using acoustic input (B6) Borschinger & Johnson 2011: particle filter for Bayesian seg (B7) Phillips & Pearl 2014a, 2014b, 2015 Ms.: cross-linguistic Bayesian segmentation (B8) Phillips & Pearl 2015: utility of segmentation output (B9) Boerschinger et al. 2012: input size effects (B10) Doyle & Levy 2013: learning stress patterns and segmenting at the same time (Bayesian) (B11) Boerschinger & Johnson 2014: inferring stress constraints |
Message board discussion points due |
| 10/13/15 |
Word meaning: Non-Overlapping Concepts [Colin] |
* (1) Frank,
Goodman, & Tenenbaum 2009 Background (A1) Swingley 2012: intro to word meaning learning, from the cog dev perspective Experimental (B1) Bergelson & Swingley 2012, 2014, 2015: early word learning (B2) Graf Estes et al. 2011: constraints on word labels (B3) Smith & Yu 2008: infant cross-situational learning (B4) Medina et al. 2011: against cross-situational learning (B5) Ramscar et al. 2011: for cross-situational learning, but with differences between kids and adults (B6) Kachergis et al. 2012: active vs passive learning for word-meaning mapping (B7) Yurovsky et al. 2012: word seg + word-meaning mapping in parallel (B8) Smith & Yu 2013: visual attention & local effects in cross-situational learning (B9) Yurovsky et al. 2013: utility of partial knowledge (B10) Kachergis & Yu 2013: cross sit learning without 1-1 mapping (B11) Romberg & Yu 2013: rich info structure in cross-sit learning (B12) Romberg & Yu 2014: cross-situational learning vs. hypothesis-testing Computational (C1) Frank et al. 2012: using social cues for word learning (C2) Fazly et al. 2010: probabilistic model of word-meaning mapping for more than just nouns (C3) Stevens et al. 2013: pursuit of word meanings (word-meaning mapping) + word-learning commentary (C4) Nematzadeh 2010: multi-word acq model (C5) Nematzadeh et al. 2011: word learning + sem cat in late talkers (C6) Nematzadeh et al. 2012: memory, attention, & word learning (C7) Lewis & Frank 2013: Bayesian model of concept learning and word-concept mapping (follow-up for Frank et al. 2009) (C8) Carstensen et al. 2014: rational model word-learning spatial relationships (extension of Frank et al. 2009) (C9) Mollica & Piantadosi 2015: word learning cross-sit with recursion |
Message board discussion points due |
| 10/15/15 |
Word Meaning: Overlapping Concepts [Prutha] |
* (1) Xu
& Tenenbaum 2007 Computational (A1) Gagliardi et al. 2012: incorporating grammatical category information (A2) Jenkins et al. 2015: non-Bayes word learning for overlapping concepts (experimental + computational) (A3) Meylan & Griffiths 2015: learning words from multiword utterances - Xu & Tenenbaum 2007 extension |
Message board discussion points due |
| 10/20/15 |
Grammatical Categories [Galia] |
* (1) Mintz
2003 Experimental (A1) Mintz 2006: infant sensitivity to FFs (A2) Syrett & Lidz 2010, Syrett et al. 2014: identifying more complex grammatical category information (A3) Lany & Saffran 2011: other cues to grammatical category that children use Computational (B1) Wang & Mintz 2010: why FFs work (B2) Chemla et al. 2009: the importance of frames vs. trigrams, FFs in other languages (B3) Weisleder & Waxman 2010: Spanish FFs (B4) St.Clair et al. 2010: Flexible frames (Mintz 2003 followup) (B5) Stumper et al. 2011: German FFs (B6) Liebbrandt & Powers 2010: Issues with Dutch FFs (B7) Wang & Mintz 2008: online learning of FFs (B8) Freudenthal et al. 2013: FF comparison with other framing metrics (B9) Goldwater & Griffiths 2007: Bayesian categorization (ideal learner) |
Message board discussion points due |
| 10/22/15 |
Morphology
[Blair] |
* (1) Gagliardi
et al. 2012 Experimental (A1) Gagliardi & Lidz 2014: noun classification data (A2) Demuth & Weschler 2012: noun classification in Sesotho + acquisition |
Message board discussion points due |
| 10/27/15 |
Morphosyntax [Alandi] |
* (1) Yang 2010
Ms * (2) Faculty of Language commentary Background (A1) Piantadosi 2014: Zipf's law (A2) Zipf's law video Computational/Corpus (B1) Yang 2011: shorter version of Yang 2010 Ms (B2) Kowalski & Yang 2012: child vs adult usage of verbs (B3) Yang 2013: productivity in children vs great apes (B4) Pine et al. 2013: productivity in determiners (response to Yang 2013) |
Message board discussion points due |
| 10/29/15 |
Poverty of the Stimulus I: Intro [Lisa] |
* (1) Gerken
2006 * (2) Gerken 2010 Background (A1) Pinker 2004: overview of poverty of the stimulus (A2) Yang posts on positive & negative evidence at the Faculty of Language blog: 1, 2, 3 Experimental (B1) Mueller et al. 2012: development of rule-learning in infants with auditory perception roots (B2) Gervain & Werker 2013: non-adjacent rule learning in 7-month-olds |
Message board discussion points due |
| 11/3/15 |
Poverty of the Stimulus II: Against [Ryan] |
* (1) Pullum
& Scholz 2002 Background (A1) Crain & Pietroski 2002: difficult linguistic knowledge (A2) Pullum 2011: more recent comments on Chomky's approach to UG + Brenchley & Lobina 2011: reply to Pullum's comments + video of Chomsky's comments in London (A3) Yang 2015: The contribution of frequency in language acquisition Experimental (B1) Gamache & Schmitt 2012: compounds and issues with learning them (B2) Ramscar et al. 2013: update for pov of stim with plural overregularization (expt & comp) Computational (C1) Legate & Yang 2002: quantifying the learnability of a particular phenomenon (C2) Hsu & Chater 2010: another way to quantify the learnability of a particular phenomenon (C3) Yang 2015 Ms: A-adjectives (negative, positive evidence) |
Message board discussion points due |
| 11/5/15 |
Poverty of the Stimulus + Syntax: Structure Dependence [Prutha] |
* (1) Perfors,
Tenenbaum, & Regier 2011 Background/Theory (A1) Berwick et al. 2011: reply to Perfors, Tenenbaum, & Regier (among others) Computational (B1) Perfors, Tenenbaum, & Regier 2006: shorter version of Perfors et al. 2011 (B2) Reali & Christiansen 2005: statistical learning of y/n questions (B3) Kam et al. 2008: problems with statistical learning of y/n questions |
Message board discussion points due |
| 11/10/15 |
Poverty of the Stimulus + Syntax: Anaphoric One [K.J.] |
* (1) Pearl
& Mis in press Background (A1) Payne et al. 2013: semantics-focused account of learning anaphoric one Experimental (B1) Lidz, Waxman, & Freedman 2003: 18-month-olds know anaphoric one Computational (C1) Pearl & Mis 2011: shorter version of Pearl & Mis in press (C2) Regier & Gahl 2004: Bayesian learning of anaphoric one using ambiguous data (C3) Foraker et al. 2009: Bayesian learning of anaphoric one using linguistic knowledge (C4) Pearl & Lidz 2009: learners can only use some ambiguous data |
Message board discussion points due |
| 11/12/15 |
NO CLASS |
Be working on the reading for next time |
|
| 11/17/15 | Poverty of the Stimulus + Syntax: Syntactic Islands [Blair] |
* (1) Pearl &
Sprouse 2013 Background (A1) Phillips 2013: response to Pearl & Sprouse 2013 Experimental (B1) Gagliardi et al. 2012 Ms: acquisition of filler-gap dependencies by young children Computational (C1) Pearl & Sprouse 2013 book chapter: focused on relationship to language processing (C2) Pearl & Sprouse 2015: focused on applications in language development |
Message board discussion points due |
| 11/19/15 | Rules of Language Use [K.J.] |
* (1) Goodman
& Stuhlmuller 2013 Background (A1) McNally 2013: Semantics & pragmatics review article Computational (B1) Frank & Goodman 2012 + supplementary material: pragmatic reasoning (B2) Bergen et al. 2014: RSA + implicatures (B3) Kao et al. 2014: nonliteral understanding of number words (B4) Kao & Goodman 2015: verbal irony |
Message board discussion points due |
| 11/24/15 |
Complex Systems: Intro [Galia] |
* (1) Pearl &
Lidz 2013 Background (A1) Baker 2008: macro vs. micro parameters (A2) Lasnik & Lohndal 2010: approaches to parameters (A3) Lightfoot 2010: using cues to learn parameters (A4) O'Grady 2005 pp.120-142: Some difficult syntactic phenomena (A5) Lidz 2010: constituents, bare plurals, ditransitive verbs Experimental (B1) Nevins 2010: constraints on phonological grammars (B2) Viau & Lidz 2011: ditransitive verbs (B3) Becker & Estigarribia 2013: raising & control verbs Computational (C1) Mitchener & Becker 2011: learning about raising vs. control verbs (C2) Orita et al. 2013: pronouns with discourse info (exp + comp) |
Message board discussion points due |
| 11/26/15 |
NO CLASS Happy Thanksgiving! |
||
| 12/1/15 |
Complex Systems, Statistical Learning, & UG [Alandi] |
* (1) Lidz &
Gagliardi 2015 Background (A1) Pearl 2014: how to use modeling to tell us about UG (response to Ambridge et al. 2014) Experimental (B1) Hadley et al. 2011: support for variational learning Computational (C1) Yang 2004, 2011: UG & statistical learning (variational learner) (C2) Legate & Yang 2007: learning optional infinitives with variational learning (C3) Freudenthal et al. 2010: against variational learning for optional infinitives (C4) Freudenthal et al. 2015: MOSAIC model for OIs (C5) Pelham 2011: ambiguity makes learning more difficult (C6) Pearl 2008: unambiguous data in metrical phonology (C7) Pearl 2009, 2011: learning metrical phonology parameters (C8) Legate & Yang 2012: productivity & metrical phonology |
Message board discussion points due |
| 12/3/15 |
Peer review [Everyone] |
|
|
| 12/8/15 |
Final presentations Special time: 11:00am-12:30pm [Everyone] |
|