L1 phonotactic knowledge and the L2 acquisition of alternations

Pater, Joe; Tessier, Anne-Michelle

doi:10.1075/z.133.07pat

Cited by 26 publications

(23 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It would not show that alternations and phonotactics are necessarily computed from the same, monolithic system, as Optimality Theory asserts, but would argue that information is shared between them, at least from alternations to phonotactics. Although the findings of Pater & Tessier (2003) are suggestive, this study cannot confirm the flow of information from phonotactics to alternations. However, of the two directions of information flow, that from alternations to phonotactics is the more surprising.…”

Section: Discussioncontrasting

confidence: 71%

Does Learning Alternations Affect Phonotactic Judgments?

Pizzo¹,

Pater

2016

AMP

Self Cite

View full text Add to dashboard Cite

It has long been recognized that alternations often serve to resolve violations of the phonotactic constraints of a language, and it has often been claimed that this entails a unified analysis. However, alternations and phonotactics do not always reflect identical constraints or processes. We provide experimental evidence that the learning of an alternation may affect phonotactic judgments.Participants were trained on one of two artificial languages. Each language contained evidence for one of two alternations, while not excluding the possibility that the other alternation occurs. The constraints motivating the alternations were not violated in either language. All participants were then tested on their phonotactic preference for the sequences avoided by each alternation. Experiment 1 found a significant interaction between alternation trained on and phonotactic preference, supporting the hypothesis that the learning of an alternation to avoid a sequence reduces the phonotactic acceptability of that sequence. Experiment 2 found a nonsignificant trend in the same direction. We conclude that while further investigation is needed, there is reason to consider potential interactions between alternations and phonotactics in the modeling of phonological learning.

show abstract

Section: Discussioncontrasting

confidence: 71%

Does Learning Alternations Affect Phonotactic Judgments?

Pizzo¹,

Pater

2016

AMP

Self Cite

View full text Add to dashboard Cite

show abstract

“…A long tradition of typological research has established strong universal patterns across languages, a result that could be interpreted as favoring a system that includes a strong Universal Grammar. Recent research in artificial grammar learning has also shown that linguistic patterns that counter such universal trends are either unlearnable or at least not easily learnable (Carpenter 2006(Carpenter , 2010Coetzee 2009b;Moreton 2008;Pater and Tessier 2006). On the other hand, there are also unambiguous examples of languages with grammars that counter universal trends (Coetzee and Pretorius 2010;Hyman 2001), showing that it should be possible for language learners to acquire grammars that do not fit neatly into the limits of Universal Grammar.…”

Section: 1mentioning

confidence: 99%

Frequency biases in phonological variation

Coetzee

Kawahara

2012

Nat Lang Linguist Theory

View full text Add to dashboard Cite

Abstract. In the past two decades, variation has received a lot of attention in mainstream generative phonology, and several different models have been developed to account for variable phonological phenomena. However, all existing generative models of phonological variation account for the overall rate at which some process applies in a corpus, and therefore implicitly assume that all words are affected equally by a variable process. In this paper, we show that this is not the case. Many variable phenomena are more likely to apply to frequent than infrequent words. A model that accounts perfectly for the overall rate of application of some variable process therefore does not necessarily account very well for the actual application of the process to individual words. We illustrate this with two examples, English t/d-deletion and Japanese geminate devoicing. We then augment one existing generative model (noisy Harmonic Grammar) to incorporate the contribution of usage frequency to the application of variable processes. In this model, the influence of frequency is incorporated by scaling the weights of faithfulness constraints up or down for words of different frequencies. This augmented model accounts significantly better for variation than existing generative models.

show abstract

“…ARTIFICIAL LANGUAGE LEARNING EXPERIMENTS Although the artificial language learning paradigm does not exactly mirror natural language learning exactly, there is a growing body of research that utilizes this paradigm to investigate problems in theoretical phonology (Wilson 2006;Pater & Tessier 2006;Carpenter 2006;etc.). While acknowledging that results from such experiments should be interpreted with caution, I follow this recent trend.…”

mentioning

confidence: 99%

Learning lexical indexation

Coetzee

2009

Phonology

View full text Add to dashboard Cite

Abstract. Morphological concatenation often triggers phonological processes. For instance, addition of the plural suffix /-ǝn/ to Dutch nouns causes vowel lengthening in some nouns due to the weight-to-stress principle ([xɑt] vs. [xáː.tǝn] 'hole'). These kinds of processes often apply only to a subset of words -not all Dutch nouns undergo this process ([kɑt] vs. [kɑ.tǝn] 'cat'). Nouns need to be lexically indexed as either undergoing this process or not. I investigate how phonological grammar and lexical indexation are learned when learners are confronted with data like these. Based on learnability considerations, I hypothesize that learners acquire a grammar with default non-alternation, so that novel items are treated as non-alternating. I report the results of artificial language learning experiments compatible with this hypothesis, and model these results in a version of the Biased Constraint Demotion Algorithm (Prince and Tesar 2004).

show abstract

L1 phonotactic knowledge and the L2 acquisition of alternations

Cited by 26 publications

References 29 publications

Does Learning Alternations Affect Phonotactic Judgments?

Does Learning Alternations Affect Phonotactic Judgments?

Frequency biases in phonological variation

Learning lexical indexation

Contact Info

Product

Resources

About