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Phonological learnability deals with the formal properties of phonological languages and grammars, which are combined with algorithms that attempt to learn the language-specific aspects of those grammars. The classical learning task can be outlined as follows: Beginning at a predetermined initial state, the learner is exposed to positive evidence of legal strings and structures from the target language, and its goal is to reach a predetermined end state, where the grammar will produce or accept all and only the target language’s strings and structures. In addition, a phonological learner must also acquire a set of language-specific representations for morphemes, words and so on—and in many cases, the grammar and the representations must be acquired at the same time. Phonological learnability research seeks to determine how the architecture of the grammar, and the workings of an associated learning algorithm, influence success in completing this learning task, i.e., in reaching the end-state grammar. One basic question is about convergence: Is the learning algorithm guaranteed to converge on an end-state grammar, or will it never stabilize? Is there a class of initial states, or a kind of learning data (evidence), which can prevent a learner from converging? Next is the question of success: Assuming the algorithm will reach an end state, will it match the target? In particular, will the learner ever acquire a grammar that deems grammatical a superset of the target language’s legal outputs? How can the learner avoid such superset end-state traps? Are learning biases advantageous or even crucial to success? In assessing phonological learnability, the analysist also has many differences between potential learning algorithms to consider. At the core of any algorithm is its update rule, meaning its method(s) of changing the current grammar on the basis of evidence. Other key aspects of an algorithm include how it is triggered to learn, how it processes and/or stores the errors that it makes, and how it responds to noise or variability in the learning data. Ultimately, the choice of algorithm is also tied to the type of phonological grammar being learned, i.e., whether the generalizations being learned are couched within rules, features, parameters, constraints, rankings, and/or weightings.


Yvan Rose

Child phonology refers to virtually every phonetic and phonological phenomenon observable in the speech productions of children, including babbles. This includes qualitative and quantitative aspects of babbled utterances as well as all behaviors such as the deletion or modification of the sounds and syllables contained in the adult (target) forms that the child is trying to reproduce in his or her spoken utterances. This research is also increasingly concerned with issues in speech perception, a field of investigation that has traditionally followed its own course; it is only recently that the two fields have started to converge. The recent history of research on child phonology, the theoretical approaches and debates surrounding it, as well as the research methods and resources that have been employed to address these issues empirically, parallel the evolution of phonology, phonetics, and psycholinguistics as general fields of investigation. Child phonology contributes important observations, often organized in terms of developmental time periods, which can extend from the child’s earliest babbles to the stage when he or she masters the sounds, sound combinations, and suprasegmental properties of the ambient (target) language. Central debates within the field of child phonology concern the nature and origins of phonological representations as well as the ways in which they are acquired by children. Since the mid-1900s, the most central approaches to these questions have tended to fall on each side of the general divide between generative vs. functionalist (usage-based) approaches to phonology. Traditionally, generative approaches have embraced a universal stance on phonological primitives and their organization within hierarchical phonological representations, assumed to be innately available as part of the human language faculty. In contrast to this, functionalist approaches have utilized flatter (non-hierarchical) representational models and rejected nativist claims about the origin of phonological constructs. Since the beginning of the 1990s, this divide has been blurred significantly, both through the elaboration of constraint-based frameworks that incorporate phonetic evidence, from both speech perception and production, as part of accounts of phonological patterning, and through the formulation of emergentist approaches to phonological representation. Within this context, while controversies remain concerning the nature of phonological representations, debates are fueled by new outlooks on factors that might affect their emergence, including the types of learning mechanisms involved, the nature of the evidence available to the learner (e.g., perceptual, articulatory, and distributional), as well as the extent to which the learner can abstract away from this evidence. In parallel, recent advances in computer-assisted research methods and data availability, especially within the context of the PhonBank project, offer researchers unprecedented support for large-scale investigations of child language corpora. This combination of theoretical and methodological advances provides new and fertile grounds for research on child phonology and related implications for phonological theory.