Abstract
It has long been noted that language production seems to reflect a correlation between message redundancy and signal reduction. More frequent words and contextually predictable instances of words, for example, tend to be produced with shorter and less clear signals. The same tendency is observed in the language code (e.g. the phonological lexicon), where more frequent words and words that are typically contextually predictable tend to have fewer segments or syllables. Average predictability in context (informativity) also seems to be an important factor in understanding phonological alternations. What has received little attention so far is the relation between various information-theoretic indices – such as frequency, contextual predictability, and informativity. Although each of these indices has been associated with different theories about the source of the redundancy-reduction link, different indices tend to be highly correlated in natural language, making it difficult to tease apart their effects. We present a computational approach to this problem. We assess the correlations between frequency, predictability, and informativity, and assess when these correlations are likely to create spurious (null or non-null) effects depending on, for example, the amount of data available to the researcher.
Acknowledgement
We would like to thank Emily Gleason and Elinor Amit for their feedback.
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