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  4. Hyperarticulation aids learning of new vowels in a developmental speech acquisition model
 
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2017
Conference Paper
Title

Hyperarticulation aids learning of new vowels in a developmental speech acquisition model

Abstract
Many studies emphasize the importance of infant-directed speech: stronger articulated, higher-quality speech helps infants to better distinguish different speech sounds. This effect has been widely investigated in terms of the infant's perceptual capabilities, but few studies examined whether infant-directed speech has an effect on articulatory learning. In earlier studies, we developed a model that learns articulatory control for a 3D vocal tract model via goal babbling. Exploration is organized in the space of outcomes. This so called goal space is generated from a set of ambient speech sounds. Similarly to how speech from the environment shapes infant's speech perception, the data from which the goal space is learned shapes the later learning process: it determines which sounds the model is able to discriminate, and thus, which sounds it can eventually learn to produce. We investigate how speech sound quality in early learning affects the model's capability to learn new vowel sounds. The model is trained either on hyperarticulated (tense) or on hypoarticulated (lax) vowels. Then we retrain the model with vowels from the other set. Results show that new vowels can be acquired although they were not included in early learning. There is, however, an effect of learning order, showing that models first trained on the stronger articulated tense vowels easier accommodate to new vowel sounds later on.
Author(s)
Philippsen, A.K.
Reinhart, R.F.
Wrede, B.
Wagner, P.
Mainwork
International Joint Conference on Neural Networks, IJCNN 2017  
Conference
International Joint Conference on Neural Networks (IJCNN) 2017  
DOI
10.1109/IJCNN.2017.7965833
Language
English
Fraunhofer-Institut für Entwurfstechnik Mechatronik IEM  
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