Dual-route models remain for the most part incompletely specified. Because crucial details are missing from their specification, they have generally not been implemented as computational cognitive models. Therefore, there is far less empirical rigor in dual-route thinking. To put it starkly, dual-route proponents have conducted expensive, elaborate brain imaging studies to validate their model but have not proposed a model detailed enough to implement on a $400 laptop.

The dual-route description of the English past tense can be given as such:

1. Use associative memory to find a past tense form.
2. If this lookup fails, or times out, append /-d/ and apply phonology.

Note that this ordering is critical: one cannot ask simply ask whether a verb is regular, since by hypothesis some or all regular verbs are not stored as such. And, as we know (Berko 1958), novel and nonce verbs are almost exclusively inflected with /-d/, consistent with the current ordering.¹ This model equates—rightly, I think—the notions of regularity with the elsewhere condition. The problem is with the fuzziness in how one might reach condition (2). We do not have any notion of what it might mean for associative memory lookup to fail. Neural nets, for instance, certainly do not fail to produce an output, though they will happily produce junk in certain cases. Nor do we much of a notion of how it might time out.

I am aware of two serious attempts to spell out this crucial detail. The first is Baayen et al.’s 1997 visual word recognition study of Dutch plurals. They imagine that (1) and (2) are competing activation “routes” and that recognition occurs when either of the routes reaches activation threshold, as if both routes run in parallel. To actually fit their data, however, their model immediately spawns epicycles in the form of poorly justified hyperparameters (see their fn. 2) and as far as I know, no one has ever bothered to reuse or reimplement their model.² The second is O’Donnell’s 2015 book, which proposes a cost-benefit analysis for storage vs. computation. However, this complex  and clever model is not described in enough detail for a “white room” implementation, and no software has been provided. What dual route proponents owe us, in my opinion, is a next toolkit. Without serious investment in formal computational description and reusable, reimplementable, empirically validated models, it is hard to take the dual-route proposal seriously.

Endnotes

1. There’s a lot of work which obfuscates this point. An impression one might get from Albright & Hayes (2003) is that adult nonce word studies produce quite a bit of irregularity, but this is only true in their rating task and hardly at all in their “volunteering” (production) task, and a hybrid task finds much higher ratings for noce irregulars. Schütze (2005) argues—convincingly, in my opinion—that this is because speakers use a different task model in rating tasks, one that is mostly irrelevant to what Albright & Hayes are studying.
2. One might be tempted to fault Baayen et al. for using visual stimulus presentation (in a language with one of the more complex and opaque writing systems), or for using recognition as a proxy for production. While these are probably reasonably critiques today, visual word recognition was still the gold standard in 1997.

References

Albright, A. and Hayes, B. 2003. Rules vs. analogy in English past tenses: a computational/experimental study. Cognition 90(2): 119-161.
Baayen, R. H., Dijkstra, T., and Schreuder, R. 1997. Singulars and plurals in Dutch: evidence for a parallel dual-route model. Journal of Memory & Language 37(1): 94-117.
Berko, J. 1958. The child’s learning of English morphology. Word 14: 150-177.
O’Donnell, T. 2015. Productivity and Reuse in Language: a Theory of Linguistic Computation and Storage. MIT Press.
Schütze, C. 2005. Thinking about what we are asking speakers to do. In S. Kepser and M. Reis (ed.), Linguistic Evidence: Empirical, Theoretical, and Computational Perspectives, pages 457-485. Mouton de Gruyter.