39 D.Reirter.I.D.Moore/Journal of Memory and Language 76 (2014)29-46 en-speaker【 th 0? shown) Covariate 2 p>国 88 884 0001 .153 000 08 thke short er it domakon3cteReiethat5posib othetical lanation of our failure to find the et al 2011)The next experimer riming-task s s correlat investigates the latter possibility.Ar ogous to the previ ds It i extent such a brief effect helps align their sit adaptation relares to more task success. ong-terr uation models.In the Map Task experiments one o Method make a difference is reference to landmarks.Do interlo For structural priming,two repetition effects have beer through the intemal structure of noun phrases that iden priming effects are strong tity the landmarks ces may also be avo dd )and reach alov secon es the eftect s s that e em syntactic adapttion that on)priming ntly tha tha lends itseftoa custering of references to the sameand mate ing.have been observed for sho m priming.but not fo g-tern ma An alternative xplanationcom om the empirica ong-term stru tural adaptation effects by Ferreira and long-term persists (Ferreira After the initial few sec structural repetition ld in short 10 but mem ones of sy ooks at tition of sy ctic rules tion for the This method splits each diald ue in half Apalogous to cess to long-term adaptation the short-term priming model repetit and sample rule instances from the second docu Experiment 4:task success and long-term adaptation .10 s,10-s por Interactive alignment is a process that happens on the rder to d ish adan tation from rall.random time-scale of min utes:spe we contrast dialogue halves tially thought be based on short-term priming.Picke and Garrod (2004)do not detail the longevity of theExperiment 2 points to stronger priming in such situations. Our results are difficult to reconcile with the model sug￾gested by Pickering and Garrod (2004), if we take short￾term priming as the driving force behind the IAM. A hypothetical explanation of our failure to find the priming–task success correlation is that short-term prim￾ing decays within a few seconds. It is questionable to what extent such a brief effect helps interlocutors align their sit￾uation models. In the Map Task experiments, one of the linguistic devices where lexical alignment is expected to make a difference is reference to landmarks. Do interlocu￾tors need to refer to landmarks every few seconds? Syntac￾tic priming forms part of alignment of such references through the internal structure of noun phrases that iden￾tify the landmarks. Syntactic devices may also be avoided within the early period of rapid decay of repetition proba￾bility that we observe. We hypothesized that the syntacti￾cally more complex descriptions of how to circumnavigate the landmarks would be repeated on the order of several times a minute, but not commonly within 5–10 s. An anal￾ysis of the dialogues, however, showed that reference is used much more frequently than we expected. The task lends itself to a clustering of references to the same land￾mark, as speakers describe the route step by step. Thus, our hypothetical explanation cannot be corroborated. An alternative explanation comes from the empirical literature: there are two distinguishable, but interacting adaptation effects. A fast, short-term priming effect, and long-term adaptation that persists (Ferreira & Bock, 2006). In the cognitive model we proposed in Reitter et al. (2011), short-term priming is enhanced by semantic material held in short-term memory, but memories of syn￾tactic structures are reinforced and become increasingly more accessible with each use. This provides an explana￾tion for the observed stronger priming in task-oriented dialogue. In the next experiment, we seek to link task suc￾cess to long-term adaptation. Experiment 4: task success and long-term adaptation Interactive alignment is a process that happens on the time-scale of minutes: speakers establish a common refer￾ence system in the long run. This process may not as ini￾tially thought be based on short-term priming. Pickering and Garrod (2004) do not detail the longevity of the priming effects supporting alignment. It is unclear whether alignment is due to the automatic, classical priming effect, or whether it is based on a long-term effect that is possibly related to implicit learning (Bock & Griffin, 2000; Chang et al., 2006; Kaschak et al., 2011). The next experiment investigates the latter possibility. Analogous to the previ￾ous experiment, we hypothesize that more long-term adaptation relates to more task success. Method For structural priming,8 two repetition effects have been identified. Classical structural priming effects are strong: around 10% for syntactic rules (Reitter et al., 2006). However, they decay quickly (Branigan et al., 1999) and reach a low pla￾teau after a few seconds, which makes the effect seem similar to semantic priming. What complicates matters is that there is also a different, long-term syntactic adaptation effect that is also commonly called (repetition) priming. Structural adaptation has been shown to last longer, from minutes (Bock & Griffin, 2000) to several days. Lexical boost interactions, where the lexical repetition of material within the repeated structure strengthens structural prim￾ing, have been observed for short-term priming, but not for long-term priming trials where material intervened between prime and target utterances. Thus, short- and long-term structural adaptation effects may well be due to separate cognitive processes, as argued by Ferreira and Bock (2006). After the initial few seconds, structural repetition shows little decay, but can be demonstrated even minutes or longer after the stimulus. To measure this type of adap￾tation, this method looks at repetition of syntactic rules over whole document halves, independently of decay. This method splits each dialogue in half. Analogous to the short-term priming model, we define repetition as the occurrence of a prime within the first document half (PRIME), and sample rule instances from the second docu￾ment half. To rule out short-term priming effects, 10-s por￾tion in the middle of the dialogues is excluded. In order to distinguish adaptation from overall, random repetition of syntactic rules, we contrast dialogue halves Table 4 The full regression model for the Map Task dataset (Experiment 3). CP indicates between-speaker (comprehension-production) priming; PP is within-speaker priming. The scale of PATHDEV is in mm2 to indicate the area of path deviation in the Map Task; as centred, it ranges from 64 to þ159. All covariates were centred; fixed-effect correlations between all centred variables was lower than 0:2. Model ANOVA corroborate the significance of parameter tests (F-values shown). Covariate b SE F z pð> jzjÞ Intercept 1:747 0.174 0:014 127 < 0:0001 lnðDistÞ 0:150 0.860 0:014 86.7 10.5 < 0:0001 CP 0:364 0.695 0:020 277.6 18.2 < 0:0001 PATHDEV 0:0002 1.000 0:0002 0.153 0.81 0:42 lnðFreqÞ 0:700 2.013 0:012 3557 59.9 < 0:0001 lnðDistÞ:CP 0.911 0:093 0:024 14.5 3.91 < 0:0001 lnðDistÞ:lnðFreqÞ 0:080 1.083 0:013 39.4 6.27 < 0:0001 lnðDistÞ:PATHDEV/PP 0.000 0:0000 0:0003 0.03 0.07 0:95 lnðDistÞ:PATHDEV/CP 0.000 0:0001 0:0004 0.21 0:84 8 In both production and comprehension, which we do not distinguish further for space reasons. 38 D. Reitter, J.D. Moore / Journal of Memory and Language 76 (2014) 29–46