What does this equation mean?

While the recursion debate ran on argument and reanalysis, a separate research program was accumulating experimental results that never claimed to resolve the poverty-of-the-stimulus question but did show that infants arrive with more general-purpose statistical machinery than a strict nativist account had reason to expect. Jenny Saffran, Richard Aslin and Elissa Newport’s 1996 Science paper remains the field’s most cited demonstration. Eight-month-old infants heard two minutes of a continuous, monotone synthetic speech stream built from four made-up three-syllable “words,” with no pauses, stress cues, or other surface markers at word boundaries; the only information available to distinguish a word from a non-word was that syllables inside one of the artificial words always followed each other with a transitional probability of 1.0, while syllables that happened to fall across a word boundary followed each other with a transitional probability closer to 0.33 [ 7 ] . After just this two-minute exposure, infants tested with the head-turn preference procedure listened differently to the high-probability “words” than to equally frequent three-syllable sequences that merely straddled two words, which showed they had extracted the statistical regularity itself rather than memorizing particular sound patterns by rote [ 7 ] . The transitional probability doing the work in a design like this can be written directly: $TP(Y \mid X) = \frac{\text{frequency of } X \text{ followed by } Y}{\text{frequency of } X}$. A syllable pair inside one of the artificial words has a transitional probability at or near one; a pair straddling two words has a transitional probability closer to a third. Nothing in the design requires a grammar module, a parameter to be set, or an innate syntactic category — only a mechanism sensitive to the conditional frequency of what follows what, operating over a stream the infant has never heard before in its life.