In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in detecting their statistical properties. These processes have been taken to be independent and temporally modular, where first, elements in the stream are encoded into internal representations, and then the co‐occurrences between them are (...) computed and registered. Here, we entertain a novel hypothesis that one unifying construct—the rate of information in the sensory input—explains learning performance. This theoretical approach merges processes related to encoding of events and those related to learning their regularities into a single computational principle. We present data from two large‐scale experiments with over 800 participants tested in support for this hypothesis, showing that rate of information in a visual stream clearly predicts SL performance, and that similar rate of information values leads to similar SL performance. We discuss the implications for SL theory and its relation to regularity learning. (shrink)

Are there individual tendencies in convergence, such that some speakers consistently converge more than others? Similarly, are there natural “leaders,” speakers with whom others converge more? Are such tendencies consistent across different linguistic characteristics? We use the Switchboard Corpus to perform a large‐scale convergence study of speakers in multiple conversations with different interlocutors, across six linguistic characteristics. Because each speaker participated in several conversations, it is possible to look for individual differences in speakers' likelihood of converging and interlocutors' likelihood of (...) eliciting convergence. We only find evidence for individual differences by interlocutor, not by speaker: There are natural leaders of convergence, who elicit more convergence than others across characteristics and across conversations. The lack of similar evidence for speakers who converge more than others suggests that social factors have a stronger effect in mediating convergence than putative individual tendencies in producing convergence, or that such tendencies are characteristic‐specific. (shrink)

Studies of word predictability in context show that words in English tend to be shorter if they are predictable from the next word, and to a lesser extent, if they are predictable from the previous word. Some studies distinguish function and content words, but otherwise have not considered grammatical factors, treating all two-word sequences as comparable. Because function words are highly frequent, words occurring with them have low predictability. Highest predictability occurs within bigrams with two content words. Using the Buckeye (...) corpus, we show that content word bigrams from different constructions vary widely in predictability, with adjective–noun and noun–noun sequences (content words within a noun phrase) having the highest scores. It is known that in adjective–noun sequences, the vowel of the adjective is shorter than in other positions. We study noun–noun sequences within the noun phrase and show that the first noun is shorter than in other contexts. It follows that the shorter duration of the first word when it is predictable from the second in many cases is due to the noun phrase construction and not necessarily the regulation of duration corresponding to predictable versus unpredictable information. We conclude that predictability studies must consider the constructions words occur in. (shrink)