scholarly journals Learning Nonlocal Phonotactics in a Strictly Piecewise Probabilistic Phonotactic Model

2021 ◽  
Vol 9 ◽  
Author(s):  
Huteng Dai
Keyword(s):  
Crucial Aspect ◽  
Phonological Acquisition ◽  
Model Based ◽  
Non Local ◽  
Computational Research ◽  
Phonotactic Learning ◽  
Occurrence Patterns

Phonotactic learning is a crucial aspect of phonological acquisition and has figured significantly in computational research in phonology (Prince & Tesar 2004). However, one persistent challenge for this line of research is inducing non-local co-occurrence patterns (Hayes & Wilson 2008). The current study develops a probabilistic phonotactic model based on the Strictly Piecewise class of subregular languages (Heinz 2010). The model successfully learns both segmental and featural representations, and correctly predicts the acceptabilities of the nonce forms in Quechua (Gouskova & Gallagher 2020).

Probabilistic Feature Attention as an Alternative to Variables in Phonotactic Learning

2021 ◽  
pp. 1-56
Author(s):  
Brandon Prickett
Keyword(s):  
Experimental Work ◽  
Experimental Results ◽  
Phonological Acquisition ◽  
Novel Approach ◽  
Free Model ◽  
Cast Doubt ◽  
Feature Attention ◽  
Phonotactic Learning ◽  
Past Experimental Work ◽  
Algebraic Representations

Abstract Since Halle (1962), explicit algebraic variables (often called alpha notation) have been commonplace in phonological theory. However, Hayes and Wilson (2008) proposed a variable-free model of phonotactic learning, sparking a debate about whether such algebraic representations are necessary to capture human phonological acquisition. While past experimental work has found evidence that suggested a need for variables in models of phonology (Berent et al. 2012, Moreton 2012, Gallagher 2013), this paper presents a novel mechanism, Probabilistic Feature Attention (PFA), that allows a variable-free model of phonotactics to predict a number of these phenomena. Additionally, experimental results involving phonological generalization that cannot be explained by variables are captured by this novel approach. These results cast doubt on whether variables are necessary to capture human-like phonotactic learning and provide a useful alternative to such representations.

A New Regularization Model Based on Non-Local Means for Image Deblurring

2013 ◽  
Vol 411-414 ◽  
pp. 1164-1169 ◽  
Author(s):  
Zhi Ming Wang ◽  
Hong Bao
Keyword(s):  
Image Denoising ◽  
Processing Speed ◽  
Operator Splitting ◽  
Image Deblurring ◽  
Local Similarity ◽  
Model Based ◽  
Local Means ◽  
Ill Posed ◽  
Non Local ◽  
Local Image

Image deblurring with noise is a typical ill-posed problem needs regularization. Various regularization models were proposed during several decades study, such as Tikhonov and TV. A new regularization model based non-local similarity constrains is proposed in this paper, which used l2 non-local norms and could be easily solved by fast non-local image denoising algorithm. By combining with Bregmanrized operator splitting (BOS) algorithm, a fast and efficient iterative three step image deblurring scheme is given. Experimental results show that proposed regularization model obtained better results on ten common test images than other similar regularization model including newly proposed NLTV regularization, both in deblurring performance (PSNR and MSSIM) and processing speed.

scholarly journals A new damage model based on non-local displacements

2005 ◽  
Vol 29 (5) ◽  
pp. 473-493 ◽  
Author(s):  
Antonio Rodríguez-Ferran ◽  
Irene Morata ◽  
Antonio Huerta
Keyword(s):  
Damage Model ◽  
Model Based ◽  
Non Local

scholarly journals Syllabic patterns in the early vocalizations of Quichua children

2011 ◽  
Vol 34 (1) ◽  
pp. 111-134 ◽  
Author(s):  
CHRISTINA E. GILDERSLEEVE-NEUMANN ◽  
BARBARA L. DAVIS ◽  
PETER F. MACNEILAGE
Keyword(s):  
Perceptual Learning ◽  
English Learning ◽  
Learning Effects ◽  
Phonological Acquisition ◽  
Early Appearance ◽  
Ambient Language ◽  
Back Vowel ◽  
Language Environment ◽  
Occurrence Patterns ◽  
Production Effects

ABSTRACTTo understand the interactions between production patterns common to children regardless of language environment and the early appearance of production effects based on perceptual learning from the ambient language requires the study of languages with diverse phonological properties. Few studies have evaluated early phonological acquisition patterns of children in non-Indo-European language environments. In the current study, across- and within-syllable consonant–vowel co-occurrence patterns in babbling were analyzed for a 6-month period for seven Ecuadorean Quichua learning children who were between 9 and 17 months of age at study onset. Their babbling utterances were compared to the babbling of six English-learning children between 9 and 22 months of age. Child patterns for both languages were compared with Quichua and English ambient language patterns. Babbling output was highly similar for the child groups: Quichua and English children's babbling demonstrated similar predicted within-syllable (coronal-front vowel, labial-central vowel, dorsal-back vowel) patterns, and across-syllable manner variegation patterns for consonants. These patterns were observed at significantly greater rates in the child groups than in the respective adult language input patterns, suggesting production system influences common to children across languages rather than ambient language perceptual learning effects during these children's babbling period.

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