Karen Jesney
Biographic Data
| ID | 6223077 |
|---|---|
| NAME | Karen Jesney |
| GIVEN NAMES | Karen |
| FAMILY NAME | Jesney |
| SIGNATURE | JESNEY K |
| AFFILIATIONS | University of Southern California |
| VERIFIED | No |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 3 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
The Productive Status of Laurentian French Liaison
There are competing views in contemporary phonological theory about how to best represent processes that are pervasive, frequent, and phonologically motivated, yet still lexically sensitive. To what extent can – or should – a process that applies idiosyncratically to different morphemes, words, and even phrases, be represented in a way that allows it to generalize to novel forms? We examine this question by looking at prenominal liaison as it is …
Learning French Liaison with Gradient Symbolic Representations
Smolensky & Goldrick (2016) first made the case for Gradient Symbolic Representations (GSRs) as the inputs to phonological grammar using the phenomena of French liaison. Under this view, many common French words are stored underlyingly with partially-activated word-final consonants, and others with gradient blends of partially-activated word-initial consonants. In this paper, we follow up some of that view's predictions and consequences, focusing…
Weighted scalar constraints capture the typology of loanword adaptation
This paper discusses three basic ways in which loanwords pattern differently than native vocabulary, with a particular focus on the implicational relationships that hold among generalizations that apply at different degrees of nativization. We argue that the overall typology and the effects of the core-periphery structure are best modeled if constraints are weighted as in Harmonic Grammar (Legendre, Miyata & Smolensky 1990), and violation scores …
On the relationship between learning sequence and rate of acquisition
Many error-driven learning algorithms for constraint-based phonological grammars, including the Gradual Learning Algorithm for Optimality Theory and Harmonic Grammar, predict that more frequent input forms will be acquired earlier than less frequent input forms – a fact that has been commonly taken as a virtue of these models. These models also predict, however, that the rate of learning for more frequent input forms should be faster than the rat…
Learning in Harmonic Serialism and the necessity of a richer base
This paper reassesses the hypothesis that early phonotactic learning of constraint-based grammars relies on the Identity Map – i.e. it uses observed surface forms as the inputs which cause errors and drive learning via constraint reranking. We argue that this approach's success is closely tied to Optimality Theory's fully parallel grammatical evaluation. In the constraint-based derivational framework of Harmonic Serialism (HS; McCarthy 2000, 2007…
Biases in Harmonic Grammar
Harmonic Grammar with linear programming
Harmonic Grammar is a model of linguistic constraint interaction in which well-formedness is calculated in terms of the sum of weighted constraint violations. We show how linear programming algorithms can be used to determine whether there is a weighting for a set of constraints that fits a set of linguistic data. The associated software package OT-Help provides a practical tool for studying large and complex linguistic systems in the Harmonic Gr…
Harmonic Grammar with linear programming
Harmonic Grammar is a model of linguistic constraint interaction in which well-formedness is calculated in terms of the sum of weighted constraint violations. We show how linear programming algorithms can be used to determine whether there is a weighting for a set of constraints that fits a set of linguistic data. The associated software package OT-Help provides a practical tool for studying large and complex linguistic systems in the Harmonic Gr…
Biases in Harmonic Grammar
Learning in Harmonic Serialism and the necessity of a richer base
This paper reassesses the hypothesis that early phonotactic learning of constraint-based grammars relies on the Identity Map – i.e. it uses observed surface forms as the inputs which cause errors and drive learning via constraint reranking. We argue that this approach's success is closely tied to Optimality Theory's fully parallel grammatical evaluation. In the constraint-based derivational framework of Harmonic Serialism (HS; McCarthy 2000, 2007…
On the relationship between learning sequence and rate of acquisition
Many error-driven learning algorithms for constraint-based phonological grammars, including the Gradual Learning Algorithm for Optimality Theory and Harmonic Grammar, predict that more frequent input forms will be acquired earlier than less frequent input forms – a fact that has been commonly taken as a virtue of these models. These models also predict, however, that the rate of learning for more frequent input forms should be faster than the rat…
Weighted scalar constraints capture the typology of loanword adaptation
This paper discusses three basic ways in which loanwords pattern differently than native vocabulary, with a particular focus on the implicational relationships that hold among generalizations that apply at different degrees of nativization. We argue that the overall typology and the effects of the core-periphery structure are best modeled if constraints are weighted as in Harmonic Grammar (Legendre, Miyata & Smolensky 1990), and violation scores …
Learning French Liaison with Gradient Symbolic Representations
Smolensky & Goldrick (2016) first made the case for Gradient Symbolic Representations (GSRs) as the inputs to phonological grammar using the phenomena of French liaison. Under this view, many common French words are stored underlyingly with partially-activated word-final consonants, and others with gradient blends of partially-activated word-initial consonants. In this paper, we follow up some of that view's predictions and consequences, focusing…
The Productive Status of Laurentian French Liaison
There are competing views in contemporary phonological theory about how to best represent processes that are pervasive, frequent, and phonologically motivated, yet still lexically sensitive. To what extent can – or should – a process that applies idiosyncratically to different morphemes, words, and even phrases, be represented in a way that allows it to generalize to novel forms? We examine this question by looking at prenominal liaison as it is …
Computer Science (7 works) · Grammar (7 works) · Linguistics (7 works) · Artificial Intelligence (6 works) · Natural language processing (6 works) · Mathematics (5 works) · Phonology (5 works) · Natural Language Processing Techniques (4 works) · Philosophy (4 works) · Phonetics and Phonology Research (4 works)