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We present a straightforward and robust algorithm for periodicity detection, working in the lag (autocorrelation) domain. When it is tested for periodic signals and for signals with additive noise or jitter, it proves to be several orders of magnitude more accurate than the methods commonly used for speech analysis. This makes our method capable of(More)
Variation is controlled by the grammar, though indirectly: it follows automatically from the robustness requirement of learning. If every constraint in an Optimality-Theoretic grammar has a ranking value along a continuous scale, and the disharmony of a constraint at evaluation time is randomly distributed about this value, the phenomenon of optionality in(More)
The Gradual Learning Algorithm (Boersma 1997) is a constraint-ranking algorithm for learning optimality-theoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and Smolensky (1993, 1996, 1998,2000), which initiated the(More)
Though seemingly a good candidate for a universal output-oriented constraint, the OCP does not occur as a constraint in the production grammar. Instead, it handles, in interaction with the NoCrossing Constraint, the correspondence between acoustic cues and perceptual feature values in the perception grammar. Because faithfulness constraints use the(More)
A series of experiments shows that Spanish learners of English acquire the ship-sheep contrast in a way specific to their target dialect (Scottish or Southern British English) and that many learners exhibit a perceptual strategy found in neither Spanish nor English. To account for these facts as well as for the findings of earlier research on second(More)
We will show that the Gradual Constraint-Ranking Learning Algorithm is capable of modelling attested acquisition orders and learning curves in a realistic manner, thus bridging the gap that used to exist between formal computational learning algorithms and actual acquisition data. Levelt, Schiller, and Levelt (to appear) found that the acquisition order for(More)
This paper examines four acoustic correlates of vowel identity in Brazilian Portuguese (BP) and European Portuguese (EP): first formant (F1), second formant (F2), duration, and fundamental frequency (F0). Both varieties of Portuguese display some cross-linguistically common phenomena: vowel-intrinsic duration, vowel-intrinsic pitch, gender-dependent size of(More)
We introduce a two-stage model for the perceptual acquisition of speech sound categories within the framework of Stochastic Optimality Theory and the Gradual Learning Algorithm [1]. During the first stage, learning of language-specific sound categories by infants is driven by distributional evidence in the linguistic input. This auditory-driven learning(More)
It has been observed that grammaticality judgments do not necessarily reflect relative corpus frequencies: it is possible that structure A is judged as more grammatical than structure B, whereas at the same time structure B occurs more often in actual language data than structure A. In recent work (Boersma & Hayes 2001), we have used Stochastic Optimality(More)
This article shows that the usual speaker-based account of h-aspiré in French can explain at most three of the four phonological processes in which it is involved, whereas a listener-oriented account can explain all of them. On a descriptive level, the behaviour of h-aspiré is accounted for with a grammar model that involves a control loop, whose crucial(More)