| Literature DB >> 29061319 |
Simone Sulpizio1, Kaori Kuroda2, Matteo Dalsasso3, Tetsuya Asakawa2, Marc H Bornstein4, Hirokazu Doi2, Gianluca Esposito5, Kazuyuki Shinohara6.
Abstract
The aim of the present work was a cross-linguistic generalization of Inoue et al.'s (2011) algorithm for discriminating infant- (IDS) vs. adult-directed speech (ADS). IDS is the way in which mothers communicate with infants; it is a universal communicative property, with some cross-linguistic differences. Inoue et al. (2011) implemented a machine algorithm that, by using a mel-frequency cepstral coefficient and a hidden Markov model, discriminated IDS from ADS in Japanese. We applied the original algorithm to two other languages that are very different from Japanese - Italian and German - and then tested the algorithm on Italian and German databases of IDS and ADS. Our results showed that: First, in accord with the extant literature, IDS is realized in a similar way across languages; second, the algorithm performed well in both languages and close to that reported for Japanese. The implications for the algorithm are discussed.Entities:
Keywords: ADS; Classification; Cross-language; IDS; MFCC; Motherese
Mesh:
Year: 2017 PMID: 29061319 PMCID: PMC5910280 DOI: 10.1016/j.neures.2017.10.008
Source DB: PubMed Journal: Neurosci Res ISSN: 0168-0102 Impact factor: 3.304