Sign In

Communications of the ACM

ACM TechNews

Scientists Develop Computational Approach to Understand How Infants Perceive Language


View as: Print Mobile App Share: Send by email Share on reddit Share on StumbleUpon Share on Hacker News Share on Tweeter Share on Facebook
A mother talks to her infant.

Cognitive scientists and computational linguists have developed a quantitative modeling framework based on large-scale simulation of infants' language learning process.

Credit: goodtherapy.org

A multi-institutional team of cognitive scientists and computational linguists has developed a quantitative modeling framework based on large-scale simulation of infants' language learning process.

The approach uses machine learning to enable the systematic linkage of learning mechanisms to testable predictions about infants' attunement to native language.

The researchers trained a clustering algorithm on realistic speech input to model infants' language learning process; they fed the program spectrogram-like auditory features sampled at regular intervals obtained from naturalistic speech recordings in American English and Japanese.

This resulted in a candidate model for infants' early phonetic knowledge, which the team queried about observed differences in how Japanese- and English-learning infants discriminate speech sounds, as well as vowel- and consonant-like phonetic categories.

The model yielded positive and negative outcomes for these respective queries, suggesting current literature on early phonetic learning requires a dramatic rethink.

From News-Medical Life Sciences
View Full Article

 

Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


 

No entries found