scholarly journals Non-Concatenative Morpheme Segmentation in Adults and Children

2021 ◽  
Author(s):  
Sara Finley ◽  
Elissa Newport
Keyword(s):  
Statistical Learning ◽  
Learning Approaches ◽  
Limited Ability ◽  
Continuous Structure ◽  
School Aged Children ◽  
Adults And Children ◽  
Extended Experiment

While most morphemes in the world’s language involve continuous structure or concatenation (e.g., prefixes and suffixes), many languages show some form of non-adjacent, non-concatenative morphology. Non-concatenative morphology poses a challenge for statistical learning approaches to morpheme segmentation because the combinatorial possibilities greatly increase for non-adjacent dependencies. The present study explores the types of dependencies that human learners (school-aged children and adults) are able to extract from exposure to a miniature, artificial non-concatenative system. In Experiment 1, participants were exposed to 12 CCC ‘roots’ that fit into 72 CVCVC skeletons with a high variety of VV ‘residue’. Experiment 2 extended Experiment 1 to school-aged children (with adult controls). Experiment 3 replicated Experiment 1, but with ‘mixed’ consonant-vowel roots and residues. Across all three experiments, participants were able to recognize familiar items compared to novel items, but had limited ability to generalize the CCC roots to novel items, suggesting a limited ability to parse consonantal roots. Adults were better at generalizing to novel items compared to children.

scholarly journals Statistical language learning: computational, maturational, and linguistic constraints

2016 ◽  
Vol 8 (3) ◽  
pp. 447-461 ◽  
Author(s):  
ELISSA L. NEWPORT
Keyword(s):  
Young Children ◽  
Language Learning ◽  
Statistical Learning ◽  
Syntactic Structure ◽  
Learning Approaches ◽  
Speech Stream ◽  
Adults And Children ◽  
Language Universals ◽  
The One ◽  
Do So

abstractOur research on statistical language learning shows that infants, young children, and adults can compute, online and with remarkable speed, how consistently sounds co-occur, how frequently words occur in similar contexts, and the like, and can utilize these statistics to find candidate words in a speech stream, discover grammatical categories, and acquire simple syntactic structure in miniature languages. However, statistical learning is not merely learning the patterns presented in the input. When their input is inconsistent, children sharpen these statistics and produce a more systematic language than the one to which they are exposed. When input languages inconsistently violate tendencies that are widespread in human languages, learners shift these languages to be more aligned with language universals, and children do so much more than adults. These processes explain why children acquire language (and other patterns) more effectively than adults, and also may explain how systematic language structures emerge in communities where usages are varied and inconsistent. Most especially, they suggest that usage-based learning approaches must account for differences between adults and children in how usage properties are acquired, and must also account for substantial changes made by adult and child learners in how input usage properties are represented during learning.

Comparison of statistical learning approaches for cerebral aneurysm rupture assessment

2019 ◽  
Vol 15 (1) ◽  
pp. 141-150 ◽  
Author(s):  
Felicitas J. Detmer ◽  
Daniel Lückehe ◽  
Fernando Mut ◽  
Martin Slawski ◽  
Sven Hirsch ◽  
...  
Keyword(s):  
Cerebral Aneurysm ◽  
Statistical Learning ◽  
Aneurysm Rupture ◽  
Learning Approaches

scholarly journals THE ROLE OF PARENTS IN BOLO VILLAGE IN SUPPORTING DISTANCE LEARNING DURING THE COVID-19 PANDEMIC

2021 ◽  
Vol 4 (2) ◽  
pp. 69-75
Author(s):  
Ida Mawaddah ◽  
Zulhafriliya Zulhafriliya ◽  
Sudarsono Sudarsono
Keyword(s):  
Distance Learning ◽  
Junior High School ◽  
Healthy Lifestyle ◽  
Family Values ◽  
Learning Approaches ◽  
School Aged Children ◽  
Distant Learning ◽  
Role Of Parents ◽  
The Impact

The Indonesian government was concerned about the impact of a wider spread of Covid-19, so it moved quickly to break the chain of transmission by urging people to live a healthy lifestyle, avoid crowds, and keep a safe distance. As a result, the circumstance has a significant impact on education and learning. The goal of this study is to learn more about the role of parents in promoting distant learning and to identify the characteristics that encourage and limit distance learning in Bolo Village during the Covid-19 outbreak. Students are forced to study from home due to government regulations. Teachers can ensure students' learning activities in a variety of ways, one of which is by involving parents as the primary companion of students when they are at home. The participants in this study were parents and their junior high school-aged children. The information was gathered through organized interviews utilizing the researcher's prepared questions. The data in this study was analyzed utilizing qualitative data analysis approaches such as the Miles and Huberman model, which features a cycle that includes data reduction, data presentation, verification, and conclusion drafting. According to the findings of this study, parents in Bolo Village played four roles in supporting learning from home during the Covid-19 pandemic: 1) accompanying children in learning, 2) intense communication with children, 3) providing supervision to children, and 4) educating and supporting children motivation. The supporting variables discovered are: 1) responsibility, 2) family values, and 3) availability to satisfy the needs of children. There are also barriers, such as 1) internet network issues, 2) too much workload, and 3) boring and less diversified learning approaches.

Symbolic and Statistical Learning Approaches to Speech Summarization: A Scoping Review

2021 ◽  
pp. 101305
Author(s):  
Dana Rezazadegan ◽  
Shlomo Berkovsky ◽  
Juan C. Quiroz ◽  
A. Baki Kocaballi ◽  
Ying Wang ◽  
...  
Keyword(s):  
Statistical Learning ◽  
Scoping Review ◽  
Learning Approaches ◽  
Speech Summarization

scholarly journals Quantum Chemistry Meets Machine Learning

2019 ◽  
Vol 73 (12) ◽  
pp. 983-989 ◽  
Author(s):  
Alberto Fabrizio ◽  
Benjamin Meyer ◽  
Raimon Fabregat ◽  
Clemence Corminboeuf
Keyword(s):  
Machine Learning ◽  
Statistical Learning ◽  
Quantum Chemical ◽  
Large Scale ◽  
Organic Molecules ◽  
Chemical Properties ◽  
Learning Approaches ◽  
Energy Landscapes ◽  
Free Energy Landscapes ◽  
Large Scale Screening

In this account, we demonstrate how statistical learning approaches can be leveraged across a range of different quantum chemical areas to transform the scaling, nature, and complexity of the problems that we are tackling. Selected examples illustrate the power brought by kernel-based approaches in the large-scale screening of homogeneous catalysis, the prediction of fundamental quantum chemical properties and the free-energy landscapes of flexible organic molecules. While certainly non-exhaustive, these examples provide an intriguing glimpse into our own research efforts.

scholarly journals Statistical learning approaches in diagnosing patients with nontraumatic acute abdomen

2016 ◽  
Vol 24 ◽  
pp. 3685-3697 ◽  
Author(s):  
Gökmen ZARARSIZ ◽  
Hızır Yakup AKYILDIZ ◽  
Dinçer GÖKSÜLÜK ◽  
Selçuk KORKMAZ ◽  
Ahmet ÖZTÜRK
Keyword(s):  
Acute Abdomen ◽  
Statistical Learning ◽  
Learning Approaches

Classification of bioaccumulative and non-bioaccumulative chemicals using statistical learning approaches

2008 ◽  
Vol 12 (3-4) ◽  
pp. 157-169 ◽  
Author(s):  
Xiuli Sun ◽  
Yan Li ◽  
Xianjie Liu ◽  
Jun Ding ◽  
Yonghua Wang ◽  
...  
Keyword(s):  
Statistical Learning ◽  
Learning Approaches
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