A Law of Word Meaning in Dolphin Whistle Types

Ferrer-i-Cancho, Ramon; McCowan, Brenda

doi:10.3390/e11040688

Cited by 32 publications

(29 citation statements)

References 26 publications

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“…Qualitatively, the meaning‐frequency law defines a positive correlation between frequency and the number of meanings. Using a proxy of word meaning, the qualitative version of the law has been found in dolphin whistles (Ferrer‐i‐Cancho & McCowan, ) and in chimpanzee gestures (Hobaiter & Byrne, ). Thus, the law is a candidate for a universal property of communication.…”

Section: Introductionmentioning

confidence: 99%

The origins of Zipf's meaning‐frequency law

Ferrer-i-Cancho

Vitevitch

2018

Asso for Info Science & Tech

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In his pioneering research, G.K. Zipf observed that more frequent words tend to have more meanings, and showed that the number of meanings of a word grows as the square root of its frequency. He derived this relationship from two assumptions: that words follow Zipf's law for word frequencies (a power law dependency between frequency and rank) and Zipf's law of meaning distribution (a power law dependency between number of meanings and rank). Here we show that a single assumption on the joint probability of a word and a meaning suffices to infer Zipf's meaning‐frequency law or relaxed versions. Interestingly, this assumption can be justified as the outcome of a biased random walk in the process of mental exploration.

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Section: Introductionmentioning

confidence: 99%

The origins of Zipf's meaning‐frequency law

Ferrer-i-Cancho

Vitevitch

2018

Asso for Info Science & Tech

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“…The multiplicity of explanations for Zipf's law in a species such as dolphins depends on how many statistical features, besides Zipf's law for word frequencies, are used to break the tie between candidates. The big question that future research on dolphins whistles must address is: what is the communicative complexity of a system whose units (e.g., whistles types) are distributed following Zipf's law for word frequencies [8], show a parallel of Zipf's law of meaning distribution [11] and form sequences with correlations that defy a simple explanation such as die rolling or Simon's model? We hope that our research stimulates further data collection to determine if the rather short range correlation discovered here are an intrinsic property of dolphin whistle communication or a consequence of the small size of our dataset.…”

Section: Discussionmentioning

confidence: 99%

The span of correlations in dolphin whistle sequences

Ferrer-i-Cancho¹,

McCowan²

2012

J. Stat. Mech.

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Long-range correlations are found in symbolic sequences from human language, music and DNA. Determining the span of correlations in dolphin whistle sequences is crucial for shedding light on their communicative complexity. Dolphin whistles share various statistical properties with human words, i.e. Zipf's law for word frequencies (namely that the probability of the ith most frequent word of a text is about i −α ) and a parallel of the tendency of more frequent words to have more meanings. The finding of Zipf's law for word frequencies in dolphin whistles has been the topic of an intense debate on its implications. One of the major arguments against the relevance of Zipf's law in dolphin whistles is that is not possible to distinguish the outcome of a die rolling experiment from that of a linguistic or communicative source producing Zipf's law for word frequencies. Here we show that statistically significant whistle-whistle correlations extend back to the 2nd previous whistle in the sequence using a global randomization test and to the 4th previous whistle using a local randomization test. None of these correlations are expected by a die rolling experiment and other simple explanation of Zipf's law for word frequencies such as Simon's model that produce sequences of unpredictable elements.

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“…Although we are using human language as our guiding example, we believe that our framework does not need a mind or a brain. The theoretical framework presented is abstract enough to allow one to replace forms and meanings, respectively, by tags and resources (Cattuto, Loreto, & Pietronero, 2007), call types and behavioral contexts (McCowan et al, 2002;Ferrer-i-Cancho & McCowan, 2009), or codons and amino acids (Bel-Enguix & Jiménez-López 2011;Obst et al, 2009).…”

Section: A Functional Information Theoretic Frameworkmentioning

confidence: 99%

Optimization Models of Natural Communication

Ferrer-i-Cancho

2017

Journal of Quantitative Linguistics

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A family of information theoretic models of communication was introduced more than a decade ago to explain the origins of Zipf's law for word frequencies. The family is a based on a combination of two information theoretic principles: maximization of mutual information between forms and meanings and minimization of form entropy. The family also sheds light on the origins of three other patterns: the principle of contrast, a related vocabulary learning bias and the meaning-frequency law. Here two important components of the family, namely the information theoretic principles and the energy function that combines them linearly, are reviewed from the perspective of psycholinguistics, language learning, information theory and synergetic linguistics. The minimization of this linear function is linked to the problem of compression of standard information theory and might be tuned by self-organization.

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A Law of Word Meaning in Dolphin Whistle Types

Cited by 32 publications

References 26 publications

The origins of Zipf's meaning‐frequency law

The origins of Zipf's meaning‐frequency law

The span of correlations in dolphin whistle sequences

Optimization Models of Natural Communication

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