A “Bat” Is Easier to Learn than a “Tab”: Effects of Relative Phonotactic Frequency on Infant Word Learning

Abstract

Many studies have shown that during the first year of life infants start learning the prosodic, phonetic and phonotactic properties of their native language. In parallel, infants start associating sound sequences with semantic representations. However, the question of how these two processes interact remains largely unknown. The current study explores whether (and when) the relative phonotactic probability of a sound sequence in the native language has an impact on infants’ word learning. We exploit the fact that Labial-Coronal (LC) words are more frequent than Coronal-Labial (CL) words in French, and that French-learning infants prefer LC over CL sequences at 10 months of age, to explore the possibility that LC structures might be learned more easily and thus at an earlier age than CL structures. Eye movements of French-learning 14- and 16-month-olds were recorded while they watched animated cartoons in a word learning task. The experiment involved four trials testing LC sequences and four trials testing CL sequences. Our data reveal that 16-month-olds were able to learn the LC and CL words, while14-month-olds were only able to learn the LC words, which are the words with the more frequent phonotactic pattern. The present results provide evidence that infants’ knowledge of their native language phonotactic patterns influences their word learning: Words with a frequent phonotactic structure could be acquired at an earlier age than those with a lower probability. Developmental changes are discussed and integrated with previous findings.

Infant Recognition of Hebrew Vocalic Word Patterns

“…The present findings are in agreement with previous studies of the recognition of legal or common phonotactic patterns versus illegal or uncommon phonotactic patterns in English, Dutch, Spanish, and Catalan by 9‐ to 10‐month‐old infants, in both adjacent (Friederici & Wessels, ; Jusczyk et al., , ; Mattys et al., ; Sebastián‐Gallés & Bosch, ) and nonadjacent sequences (Gonzalez‐Gomez & Nazzi, ; Gonzalez‐Gomez et al., ; Van Kampen et al., ), and they also support previous findings with infants learning French or Turkish, showing that during the second half of their first year of life, infants recognize nonadjacent phonological dependencies that characterize word forms in their native language.…”

“…At 10 months of age, French‐learning infants showed a preference for disyllabic words containing a Labial–Coronal sequence (e.g., beta ) over words containing a Coronal–Labial sequence (e.g., tuba ) and for monosyllabic Labial‐Coronal sequences (e.g., bad ) over words containing a Coronal–Labial sequence ( dab ) (Gonzalez‐Gomez & Nazzi, ; Nazzi et al., ). Furthermore, infants learning French were able to segment Labial–Coronal sequences (nonwords, e.g., pid ) from running speech at 10 months, but Coronal–Labial sequences (e.g., dip ) only at 13 months of age, suggesting that common sequences of nonadjacent segments can serve as a cue for word segmentation in 10‐month‐olds (Gonzalez‐Gomez & Nazzi, ) and also influence early word learning (Gonzalez‐Gomez, Poltrock, & Nazzi, ).…”

Effects of Prior Phonotactic Knowledge on Infant Word Segmentation: The Case of Nonadjacent Dependencies

“…Accordingly, they found that 10-but not 6-month-old infants prefer to listen to LC words than to CL words even before they start producing LC and CL sequences . These findings establish that the LC bias cannot be only due to motor constraints but that this bias also reflects some perceptual learning of input regularities (which might indirectly reflect articulatory constraints; for further evidence, see data on Japanese adults and infants; Gonzalez-Gomez, Tsuji, Hayashi, Mazuka, & Nazzi, 2013;Tsuji, Gonzalez Gomez, Medina, Nazzi, & Mazuka, 2012).…”

Blur, eye movements and performance on a driving visual recognition slide test

“…Where interactions were significant, the simple effects were examined. Recordings of DriveSafe images that had <50% of eye tracking data were not included in the analyses, consistent with the threshold adopted by other studies using similar eye tracking systems . Twenty‐eight out of 880 slide recordings (3.2%) were excluded due to poor tracking; of those that were analysed, the mean eye tracking data recorded was 91.3% (S.D.…”