Brandon Prickett
Biographic Data
| ID | 826374 |
|---|---|
| NAME | Brandon Prickett |
| GIVEN NAMES | Brandon |
| FAMILY NAME | Prickett |
| SIGNATURE | PRICKETT B |
| AFFILIATIONS | University of Massachusetts Amherst |
| ORCID | 0000-0001-9217-2130 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Learning and generalizing stress patterns with a sequence-to-sequence neural network
We present the first application of modern neural networks to the well-studied task of learning word stress systems. We tested our adaptation of a sequence-to-sequence network on the Tesar and Smolensky (2000. Learnability in optimality theory . Cambridge, MA: MIT Press) test set of 124 “languages”, showing that it acquires generalizable representations of stress patterns in a very high proportion of runs. We also show that the neural network can…
Type and token frequency jointly drive learning of morphology
Is Sour Grapes Learnable? A Computational and Experimental Approach
In this paper, I present results from simulations using three different maximum entropy phonotactic models (Hayes & Wilson, 2008; Moreton et al., 2017): one that can only represent Sour Grapes, one that can only represent standard, attested harmony, and one that has the expressive power to capture both patterns. I then present results from an experiment designed to test the predictions of these models and find that humans behave most like the mod…
Probabilistic Feature Attention as an Alternative to Variables in Phonotactic Learning
Since Halle 1962, explicit algebraic variables (often called alpha notation) have been commonplace in phonological theory. However, Hayes and Wilson (2008) proposed a variable-free model of phonotactic learning, sparking a debate about whether such algebraic representations are necessary to capture human phonological acquisition. While past experimental work has found evidence that suggested a need for variables in models of phonology (Berent et …
Typological gaps in iambic nonfinality correlate with learning difficulty
This paper discusses gaps in stress typology that are unexpected from the perspective of a foot-based theory and shows that the patterns pose difficulties for a computationally implemented learning algorithm. The unattested patterns result from combining theoretical elements whose effects are generally well-attested, including iambic footing, nonfinality, word edge alignment and a foot binarity requirement. The patterns can be found amongst the 1…
Learning Repetition, but not Syllable Reversal
Reduplication is common, but analogous reversal processes are rare, even though reversal, which involves nested rather than crossed dependencies, is less complex on the Chomsky hierarchy. We hypothesize that the explanation is that repetitions can be recognized when they match and reactivate a stored trace in short-term memory, but recognizing a reversal requires rearranging the input in working memory before attempting to match it to the stored …
Modeling the Acquisition of Phonological Interactions: Biases and Generalization
In this paper we computationally implement four different theories for representing opaque and transparent phonological interactions: Harmonic Serialism, Stratal OT, Two-Level Constraints, and Indexed Constraints. We then show that these theories make unique predictions on two tasks: (1) a learning-bias task, based on previous experimental work with humans and (2) a novel generalization task that no human data exists for. Our results in (1) show …
Variables Must be Limited to a Single Feature
In this paper, I show that applying variables in the unconstrainted way that Halle (1962) first proposed causes the representation of certain phonotactic patterns to be simplified. I go on to show that this simplification prohibits an otherwise standard MaxEnt model from being biased in ways that reflect human behavior. As a solution, I propose limiting variables to occurring in the same feature across different segments. This not only prevents t…
Learning biases in opaque interactions
This study uses an artificial language learning experiment and computational modelling to test Kiparsky's claims about Maximal Utilisation and Transparency biases in phonological acquisition. A Maximal Utilisation bias would prefer phonological patterns in which all rules are maximally utilised, and a Transparency bias would prefer patterns that are not opaque. Results from the experiment suggest that these biases affect the learnability of speci…
Complexity and naturalness biases in phonotactics: Hayes and White (2013) revisited
Hayes and White (2013) found that English speakers rate words that violate natural phonotactic constraints as worse than words that violate unnatural ones. Their “natural” constraints both enforced typologically common restrictions and were phonetically grounded, while their unnatural constraints met neither criterion. They used this experimental finding as evidence for a learning bias in favor of natural constraints. The strength of this conclus…
Emergent positional privilege in novel English blends
We present evidence from experiments on novel blend formation showing that adult English speakers have access to constraints that give phonological privilege to HEADS, NOUNS, and PROPER NOUNS, even though the nonblend phonology provides no evidence that such constraints are generally active in the grammar of English. Our results (i) demonstrate that these positional constraints are universally available; (ii) confirm that the lexical category ‘pr…
Emergent positional privilege in novel English blends
We present evidence from experiments on novel blend formation showing that adult English speakers have access to constraints that give phonological privilege to HEADS, NOUNS, and PROPER NOUNS, even though the nonblend phonology provides no evidence that such constraints are generally active in the grammar of English. Our results (i) demonstrate that these positional constraints are universally available; (ii) confirm that the lexical category ‘pr…
Emergent positional privilege in novel English blends
We present evidence from experiments on novel blend formation showing that adult English speakers have access to constraints that give phonological privilege to HEADS, NOUNS, and PROPER NOUNS, even though the nonblend phonology provides no evidence that such constraints are generally active in the grammar of English. Our results (i) demonstrate that these positional constraints are universally available; (ii) confirm that the lexical category ‘pr…
Complexity and naturalness biases in phonotactics: Hayes and White (2013) revisited
Hayes and White (2013) found that English speakers rate words that violate natural phonotactic constraints as worse than words that violate unnatural ones. Their “natural” constraints both enforced typologically common restrictions and were phonetically grounded, while their unnatural constraints met neither criterion. They used this experimental finding as evidence for a learning bias in favor of natural constraints. The strength of this conclus…
Learning biases in opaque interactions
This study uses an artificial language learning experiment and computational modelling to test Kiparsky's claims about Maximal Utilisation and Transparency biases in phonological acquisition. A Maximal Utilisation bias would prefer phonological patterns in which all rules are maximally utilised, and a Transparency bias would prefer patterns that are not opaque. Results from the experiment suggest that these biases affect the learnability of speci…
Variables Must be Limited to a Single Feature
In this paper, I show that applying variables in the unconstrainted way that Halle (1962) first proposed causes the representation of certain phonotactic patterns to be simplified. I go on to show that this simplification prohibits an otherwise standard MaxEnt model from being biased in ways that reflect human behavior. As a solution, I propose limiting variables to occurring in the same feature across different segments. This not only prevents t…
Learning Repetition, but not Syllable Reversal
Reduplication is common, but analogous reversal processes are rare, even though reversal, which involves nested rather than crossed dependencies, is less complex on the Chomsky hierarchy. We hypothesize that the explanation is that repetitions can be recognized when they match and reactivate a stored trace in short-term memory, but recognizing a reversal requires rearranging the input in working memory before attempting to match it to the stored …
Modeling the Acquisition of Phonological Interactions: Biases and Generalization
In this paper we computationally implement four different theories for representing opaque and transparent phonological interactions: Harmonic Serialism, Stratal OT, Two-Level Constraints, and Indexed Constraints. We then show that these theories make unique predictions on two tasks: (1) a learning-bias task, based on previous experimental work with humans and (2) a novel generalization task that no human data exists for. Our results in (1) show …
Typological gaps in iambic nonfinality correlate with learning difficulty
This paper discusses gaps in stress typology that are unexpected from the perspective of a foot-based theory and shows that the patterns pose difficulties for a computationally implemented learning algorithm. The unattested patterns result from combining theoretical elements whose effects are generally well-attested, including iambic footing, nonfinality, word edge alignment and a foot binarity requirement. The patterns can be found amongst the 1…
Is Sour Grapes Learnable? A Computational and Experimental Approach
In this paper, I present results from simulations using three different maximum entropy phonotactic models (Hayes & Wilson, 2008; Moreton et al., 2017): one that can only represent Sour Grapes, one that can only represent standard, attested harmony, and one that has the expressive power to capture both patterns. I then present results from an experiment designed to test the predictions of these models and find that humans behave most like the mod…
Probabilistic Feature Attention as an Alternative to Variables in Phonotactic Learning
Since Halle 1962, explicit algebraic variables (often called alpha notation) have been commonplace in phonological theory. However, Hayes and Wilson (2008) proposed a variable-free model of phonotactic learning, sparking a debate about whether such algebraic representations are necessary to capture human phonological acquisition. While past experimental work has found evidence that suggested a need for variables in models of phonology (Berent et …
Learning and generalizing stress patterns with a sequence-to-sequence neural network
We present the first application of modern neural networks to the well-studied task of learning word stress systems. We tested our adaptation of a sequence-to-sequence network on the Tesar and Smolensky (2000. Learnability in optimality theory . Cambridge, MA: MIT Press) test set of 124 “languages”, showing that it acquires generalizable representations of stress patterns in a very high proportion of runs. We also show that the neural network can…
Type and token frequency jointly drive learning of morphology
Computer Science (10 works) · Phonetics and Phonology Research (8 works) · Artificial Intelligence (7 works) · Linguistics (7 works) · Cognitive psychology (6 works) · Psychology (6 works) · Natural language processing (5 works) · Philosophy (5 works) · Phonology (5 works) · Speech and dialogue systems (5 works)