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.
Jane Chandlee and Jeffrey Heinz
Computational phonology studies the nature of the computations necessary and sufficient for characterizing phonological knowledge. As a field it is informed by the theories of computation and phonology.
The computational nature of phonological knowledge is important because at a fundamental level it is about the psychological nature of memory as it pertains to phonological knowledge. Different types of phonological knowledge can be characterized as computational problems, and the solutions to these problems reveal their computational nature. In contrast to syntactic knowledge, there is clear evidence that phonological knowledge is computationally bounded to the so-called regular classes of sets and relations. These classes have multiple mathematical characterizations in terms of logic, automata, and algebra with significant implications for the nature of memory. In fact, there is evidence that phonological knowledge is bounded by particular subregular classes, with more restrictive logical, automata-theoretic, and algebraic characterizations, and thus by weaker models of memory.
Connectionism is an important theoretical framework for the study of human cognition and behavior. Also known as Parallel Distributed Processing (PDP) or Artificial Neural Networks (ANN), connectionism advocates that learning, representation, and processing of information in mind are parallel, distributed, and interactive in nature. It argues for the emergence of human cognition as the outcome of large networks of interactive processing units operating simultaneously. Inspired by findings from neural science and artificial intelligence, connectionism is a powerful computational tool, and it has had profound impact on many areas of research, including linguistics. Since the beginning of connectionism, many connectionist models have been developed to account for a wide range of important linguistic phenomena observed in monolingual research, such as speech perception, speech production, semantic representation, and early lexical development in children. Recently, the application of connectionism to bilingual research has also gathered momentum. Connectionist models are often precise in the specification of modeling parameters and flexible in the manipulation of relevant variables in the model to address relevant theoretical questions, therefore they can provide significant advantages in testing mechanisms underlying language processes.