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24
On languages piecewise testable in the strict sense
- In Proceedings of the 11th Meeting of the Assocation for Mathematics of Language
, 2009
"... Abstract. In this paper we explore the class of Strictly Piecewise languages, originally introduced to characterize long-distance phonotactic patterns by Heinz [1] as the Precedence Languages. We provide a series of equivalent abstract characterizations, discuss their basic properties, locate them r ..."
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Abstract. In this paper we explore the class of Strictly Piecewise languages, originally introduced to characterize long-distance phonotactic patterns by Heinz [1] as the Precedence Languages. We provide a series of equivalent abstract characterizations, discuss their basic properties, locate them relative to other well-known subregular classes and provide algorithms for translating between the grammars defined here and finite state automata as well as an algorithm for deciding whether a regular language is Strictly Piecewise. 1
Improving Word Segmentation by Simultaneously Learning Phonotactics
- CONLL 2008
, 2008
"... The most accurate unsupervised word segmentation systems that are currently available (Brent, 1999; Venkataraman, 2001; Goldwater, 2007) use a simple unigram model of phonotactics. While this simplifies some of the calculations, it overlooks cues that infant language acquisition researchers have sho ..."
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The most accurate unsupervised word segmentation systems that are currently available (Brent, 1999; Venkataraman, 2001; Goldwater, 2007) use a simple unigram model of phonotactics. While this simplifies some of the calculations, it overlooks cues that infant language acquisition researchers have shown to be useful for segmentation (Mattys et al., 1999; Mattys and Jusczyk, 2001). Here we explore the utility of using bigram and trigram phonotactic models by enhancing Brent’s (1999) MBDP-1 algorithm. The results show the improved MBDP-Phon model outperforms other unsupervised word segmentation systems (e.g., Brent, 1999; Venkataraman, 2001; Goldwater, 2007).
On the role of locality in learning stress patterns
- Phonology
, 2009
"... This paper presents a previously unnoticed universal property of stress patterns in the world's languages : they are, for small neighbourhoods, neighbourhooddistinct. Neighbourhood-distinctness is a locality condition defined in automatatheoretic terms. This universal is established by examini ..."
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This paper presents a previously unnoticed universal property of stress patterns in the world's languages : they are, for small neighbourhoods, neighbourhooddistinct. Neighbourhood-distinctness is a locality condition defined in automatatheoretic terms. This universal is established by examining stress patterns contained in two typological studies. Strikingly, many logically possible -but unattested -patterns do not have this property. Not only does neighbourhooddistinctness unite the attested patterns in a non-trivial way, it also naturally provides an inductive principle allowing learners to generalise from limited data. A learning algorithm is presented which generalises by failing to distinguish sameneighbourhood environments perceived in the learner's linguistic input -hence learning neighbourhood-distinct patterns -as well as almost every stress pattern in the typology. In this way, this work lends support to the idea that properties of the learner can explain certain properties of the attested typology, an idea not straightforwardly available in optimality-theoretic and Principle and Parameter frameworks.
The Third Factor in Phonology
- Biolinguistics
, 2009
"... This article attempts to investigate how much of phonology can be explained by properties of general cognition and the Sensorimotor system — in other words, third-factor principles, in support of the evolutionary scenario posed by Hauser et al. (2002a). It argues against Pinker & Jackendoff’s (2 ..."
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This article attempts to investigate how much of phonology can be explained by properties of general cognition and the Sensorimotor system — in other words, third-factor principles, in support of the evolutionary scenario posed by Hauser et al. (2002a). It argues against Pinker & Jackendoff’s (2005: 212) claim that “major characteristics of phonology are specific to language (or to language & music), [and] uniquely human, ” and their conclusion that “phonology represents a major counterexample to the recursion-only hypothesis. ” Contrary to the statements by Anderson (2004) and Yip (2006a, 2006b) to the effect that phonology has not been tested in animals, it is shown that virtually all the abilities that underlie phonological competence have been shown in other species.
Deciding strictly local (SL) languages
- In J. Breitenbucher (Ed.), Proceedings of the
, 2009
"... We have developed an efficient algorithm for determining if a Finite State Automaton de-scribes a Strictly Local (SL) stringset, the sim-plest class of the Sub-Regular Hierarchy, and to determine if that stringset is a subclass of SL that is learnable by an Inductive Inference Machine. We have used ..."
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We have developed an efficient algorithm for determining if a Finite State Automaton de-scribes a Strictly Local (SL) stringset, the sim-plest class of the Sub-Regular Hierarchy, and to determine if that stringset is a subclass of SL that is learnable by an Inductive Inference Machine. We have used this to categorize the phonotactic patterns in a catalog including es-sentially all of the currently attested patterns occurring in natural languages, most of which turn out to be learnable stringsets in this sim-plest class. 1
Three Correlates of the Typological Frequency of Quantity-Insensitive Stress Systems
"... We examine the typology of quantityinsensitive (QI) stress systems and ask to what extent an existing optimality theoretic model of QI stress can predict the observed typological frequencies of stress patterns. We find three significant correlates of pattern attestation and frequency: the trigram en ..."
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We examine the typology of quantityinsensitive (QI) stress systems and ask to what extent an existing optimality theoretic model of QI stress can predict the observed typological frequencies of stress patterns. We find three significant correlates of pattern attestation and frequency: the trigram entropy of a pattern, the degree to which it is “confusable” with other patterns predicted by the model, and the number of constraint rankings that specify the pattern. 1
Cognitive and Sub-Regular Complexity
"... Abstract. We present a measure of cognitive complexity for subclasses of the regular languages that is based on model-theoretic complexity rather than on description length of particular classes of grammars or automata. Unlikedescriptionlengthapproaches,thiscomplexitymeasure is independent of the im ..."
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Abstract. We present a measure of cognitive complexity for subclasses of the regular languages that is based on model-theoretic complexity rather than on description length of particular classes of grammars or automata. Unlikedescriptionlengthapproaches,thiscomplexitymeasure is independent of the implementation details of the cognitive mechanism. Hence, it provides a basis for making inferences about cognitive mechanisms that are valid regardless of how those mechanisms are actually realized. 1
Learning left-to-right and right-to-left iterative languages
"... Abstract. The left-to-right and right-to-left iterative languages are previously unnoticed subclasses of the regular languages of infinite size that are identifiable in the limit from positive data. Essentially, these language classes are the ones obtained by merging final states in a prefix tree an ..."
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Abstract. The left-to-right and right-to-left iterative languages are previously unnoticed subclasses of the regular languages of infinite size that are identifiable in the limit from positive data. Essentially, these language classes are the ones obtained by merging final states in a prefix tree and initial states in a suffix tree of the observed sample, respectively. Strikingly, these classes are also transparently related to the zero-reversible languages because some algorithms that learn them differ minimally from the ZR algorithm given in Angluin (1982). Second, they are part of the answer to the challenge provided by Muggleton (1990), who proposed mapping the space of language classes obtainable by a general statemerging algorithm IM1. Third, these classes are relevant to a hypothesis of how children can acquire sound patterns of their language—in particular, the hypothesis that all phonotactic patterns found in natural language are neighborhood-distinct (Heinz 2007). 1
Learning and learnability in phonology
"... A central scientific problem in phonology is how children rapidly and accurately acquire the intricate structures and patterns seen in the phonology of their native language. The solution to this problem lies in part in the discovery of the right formal theory of phonology, but another crucial eleme ..."
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A central scientific problem in phonology is how children rapidly and accurately acquire the intricate structures and patterns seen in the phonology of their native language. The solution to this problem lies in part in the discovery of the right formal theory of phonology, but another crucial element is the development of theories of learning, often in the form of machineimplemented models that attempt to mimic human childrens’ ability. This chapter is a survey of work in this area.
