Abstract

Computational phonology is not one thing. Rather, it is an umbrella term which may refer to work on formal language theory, computer-implemented models of cognitive processes, and corpus methods derived from the literature on natural language processing (NLP). This article gives an overview of these distinct areas, identifying commonalities and differences in the goals of each area, as well as highlighting recent results of interest. The overview is necessarily brief and subjective. Broadly speaking, it is argued that learning is a pervasive theme in these areas, but the core questions and concerns vary too much to define a coherent field. Computational phonologists are more united by a shared body of formal knowledge than they are by a shared sense of what the important questions are.

Highlights

  • What does it mean to be a scientific field of inquiry? Proceeding inductively, we might observe that well-established fields tend to exhibit the following properties: (i) a core set of observable phenomena, which the field seeks to explain (ii) a core set of research questions the field asks about those phenomena (iii) a shared set of background knowledge that is in part specific to the field (iv) a shared 'toolbox' of research methods used for gaining new knowledge

  • Readers who wish to learn more are advised to peruse a source devoted to formal language theory: Heinz (2011ab) for phonology Stabler (2009) for a survey of formal language theory as it relates to natural language universals, or an introductory computer science textbook for the basics

  • I will briefly describe two concepts which originated from Natural Language Processing (NLP)/Automatic Speech Recognition (ASR) but which have spread to computational linguistic in general

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Summary

INTRODUCTION

What does it mean to be a scientific field of inquiry? Proceeding inductively, we might observe that well-established fields tend to exhibit the following properties:. (i) a core set of observable phenomena, which the field seeks to explain (ii) a core set of research questions the field asks about those phenomena (iii) a shared set of background knowledge that is in part specific to the field (iv) a shared 'toolbox' of research methods used for gaining new knowledge. Fields can occasionally form, or shift dramatically in character, with the emergence of a charismatic and persuasive thinker or a seminal publication This was arguably the case in linguistics with Chomsky's review of B. The phrase 'computational phonology' is used as an umbrella term for research which generally presupposes a shared, specific set of background knowledge and uses a common set of research methodologies, but often with radically diverging questions. Prior to the body of the paper I briefly review background material

What is phonology?
Markedness
Alternations
Opacity
Optimality Theory
Harmonic Grammar
Probability
Odds and log-odds
Log-linear models
FORMAL LANGUAGE THEORY
General overview
The Chomsky Hierarchy
Context-free languages
Regular languages
Context-sensitive languages
Equivalency of Finite State Automata and Regular Languages
Framework comparison
Finite-state OT
Zipfian distributions
Statistical models
COGNITIVE MODELING
Phonotactic and phonological learning
Factoring the learning problem
Learnability proofs for constraints
Stochastic phonology
Constraint-based stochastic phonology
Word segmentation
CORPUS STUDIES
SUMMARY AND CONCLUSIONS

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