When statistics collide: The use of transitional and phonotactic probability cues to word boundaries

Autor(es)

Dal Ben, Rodrigo ^{[1, 2]} ; Souza, Debora de Hollanda ^[1] ; Hay, Jessica F. ^[3]

Afiliação do(s) autor(es)

^[1] Univ Fed Sao Carlos, Dept Psychol, Sao Carlos, SP - Brazil

^[2] Univ Fed Sao Carlos, Ctr Ciencias Humanas, Programa Posgrad Psicol, Via Washington Luis, Km 235, Caixa Postal 676, BR-13565905 Sao Carlos, SP - Brazil

^[3] Univ Tennessee, Dept Psychol, Knoxville, TN 37996 - USA

• Tipo de documento: Artigo Científico
• Fonte: MEMORY & COGNITION; v. 49, n. 7, p. 1300-1310, OCT 2021.
• Citações Web of Science: 0

Resumo

Statistical regularities in linguistic input, such as transitional probability and phonotactic probability, have been shown to promote speech segmentation. It remains unclear, however, whether or how the combination of transitional probabilities and subtle phonotactic probabilities influence segmentation. The present study provides a fine-grained investigation of the effects of such combined statistics. Adults (N = 81) were tested in one of two conditions. In the Anchor condition, they heard a continuous stream of words with small differences in phonotactic probabilities. In the Uniform condition, all words had comparable phonotactic probabilities. In both conditions, transitional probability was stronger in words than in part-words. Only participants from the Anchor condition preferred words at test, indicating that the combination of transitional probabilities and subtle phonotactic probabilities may facilitate speech segmentation. We discuss the methodological implications of our findings, which demonstrate that even small phonotactic variations should be accounted for when investigating statistical speech segmentation. (AU)

• Processo FAPESP: 18/04226-7 - Segmentação de fala e aprendizagem de palavras entre tentativas em paralelo
• Beneficiário: Rodrigo Dal Ben de Souza
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado