Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8842045 | Neuroscience Research | 2018 | 27 Pages |
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.
Related Topics
Life Sciences
Neuroscience
Neuroscience (General)
Authors
Simone Sulpizio, Kaori Kuroda, Matteo Dalsasso, Tetsuya Asakawa, Marc H. Bornstein, Hirokazu Doi, Gianluca Esposito, Kazuyuki Shinohara,