Early Acquisition of Plural Morphology in a Classifier Language: Data from Korean 2-4 Year Olds

2021 ◽  
pp. 1-15
Author(s):  
Dorothy Ahn ◽  
Jesse Snedeker
Keyword(s):  
Language Data ◽  
Early Acquisition

Machine-Scored Syntax: Comparison of the CLAN Automatic Scoring Program to Manual Scoring

2020 ◽  
Vol 51 (2) ◽  
pp. 479-493
Author(s):  
Jenny A. Roberts ◽  
Evelyn P. Altenberg ◽  
Madison Hunter
Keyword(s):  
Data Exchange ◽  
Child Language ◽  
Exchange System ◽  
Absolute Point ◽  
Language Analysis ◽  
Search Patterns ◽  
Language Data ◽  
Report Accuracy ◽  
Point To Point ◽  
Automatic Scoring

Purpose The results of automatic machine scoring of the Index of Productive Syntax from the Computerized Language ANalysis (CLAN) tools of the Child Language Data Exchange System of TalkBank (MacWhinney, 2000) were compared to manual scoring to determine the accuracy of the machine-scored method. Method Twenty transcripts of 10 children from archival data of the Weismer Corpus from the Child Language Data Exchange System at 30 and 42 months were examined. Measures of absolute point difference and point-to-point accuracy were compared, as well as points erroneously given and missed. Two new measures for evaluating automatic scoring of the Index of Productive Syntax were introduced: Machine Item Accuracy (MIA) and Cascade Failure Rate— these measures further analyze points erroneously given and missed. Differences in total scores, subscale scores, and individual structures were also reported. Results Mean absolute point difference between machine and hand scoring was 3.65, point-to-point agreement was 72.6%, and MIA was 74.9%. There were large differences in subscales, with Noun Phrase and Verb Phrase subscales generally providing greater accuracy and agreement than Question/Negation and Sentence Structures subscales. There were significantly more erroneous than missed items in machine scoring, attributed to problems of mistagging of elements, imprecise search patterns, and other errors. Cascade failure resulted in an average of 4.65 points lost per transcript. Conclusions The CLAN program showed relatively inaccurate outcomes in comparison to manual scoring on both traditional and new measures of accuracy. Recommendations for improvement of the program include accounting for second exemplar violations and applying cascaded credit, among other suggestions. It was proposed that research on machine-scored syntax routinely report accuracy measures detailing erroneous and missed scores, including MIA, so that researchers and clinicians are aware of the limitations of a machine-scoring program. Supplemental Material https://doi.org/10.23641/asha.11984364

A Medical Text Analysis System for German - Syntax Analysis

1991 ◽  
Vol 30 (04) ◽  
pp. 275-283 ◽  
Author(s):  
P. M. Pietrzyk
Keyword(s):  
Text Analysis ◽  
Free Text ◽  
New Approach ◽  
Syntax Analysis ◽  
Medical Text ◽  
Medical Language ◽  
Computerized Processing ◽  
Language Data ◽  
Analysis System ◽  
German Syntax

Abstract:Much information about patients is stored in free text. Hence, the computerized processing of medical language data has been a well-known goal of medical informatics resulting in different paradigms. In Gottingen, a Medical Text Analysis System for German (abbr. MediTAS) has been under development for some time, trying to combine and to extend these paradigms. This article concentrates on the automated syntax analysis of German medical utterances. The investigated text material consists of 8,790 distinct utterances extracted from the summary sections of about 18,400 cytopathological findings reports. The parsing is based upon a new approach called Left-Associative Grammar (LAG) developed by Hausser. By extending considerably the LAG approach, most of the grammatical constructions occurring in the text material could be covered.

EVALD – a Pioneer Application for Automated Essay Scoring in Czech

2019 ◽  
Vol 113 (1) ◽  
pp. 9-30
Author(s):  
Kateřina Rysová ◽  
Magdaléna Rysová ◽  
Michal Novák ◽  
Jiří Mírovský ◽  
Eva Hajičová
Keyword(s):  
Czech Republic ◽  
Native Speakers ◽  
Threshold Level ◽  
Automated Essay Scoring ◽  
The Czech Republic ◽  
Linguistic Differences ◽  
Supervised Training ◽  
Language Data ◽  
Overall Performance ◽  
Essay Scoring

Abstract In the paper, we present EVALD applications (Evaluator of Discourse) for automated essay scoring. EVALD is the first tool of this type for Czech. It evaluates texts written by both native and non-native speakers of Czech. We describe first the history and the present in the automatic essay scoring, which is illustrated by examples of systems for other languages, mainly for English. Then we focus on the methodology of creating the EVALD applications and describe datasets used for testing as well as supervised training that EVALD builds on. Furthermore, we analyze in detail a sample of newly acquired language data – texts written by non-native speakers reaching the threshold level of the Czech language acquisition required e.g. for the permanent residence in the Czech Republic – and we focus on linguistic differences between the available text levels. We present the feature set used by EVALD and – based on the analysis – we extend it with new spelling features. Finally, we evaluate the overall performance of various variants of EVALD and provide the analysis of collected results.

ASIMILASI DALAM ISOLEK BONAI ULAKPATIAN

2017 ◽  
Vol 7 (2) ◽  
pp. 167
Author(s):  
Zainal Abidin
Keyword(s):  
Ethnic Group ◽  
Recording Technique ◽  
Interview Method ◽  
Language Data ◽  
Selection Of

This study aims at describing the assimilation of Bonai Ulakpatian isolect in Riau Province. This study is a linguistics research about sound changing that occurs on the different sounds to be the same sounds at the position between two vowels in the middle of a word in an isolect that is used by Bonai ethnic group in Ulakpatian Village, Rokan Hulu Regency. The data of the research is the utterances data of Bonai ethnic group community that referred to in selection of language data. The data were collected by applying interview method by using conversation and recording technique. The data were described phonetically by using IPA symbol, the data were compared with PM and made conclusion The result of the research shows that Bonai Ulakpatian isolect has four assimilation forms at the position between two vowels in the middle of a word, namely 1) PM *nd/v-v> BU [n]/v-v, 2) PM *ŋg/v-v> BU [ŋ]/v-v, 3) PM *mb/v-v> BU [m]/v-v that are total progressive assimilation and phonetics assimilation, and 4) PM *nj/v-v> BU [ñ]/v-v that are reciprocal and phonemic assimilation.AbstrakPenelitian ini bertujuan untuk mendeskripsikan asimilasi pada isolek Bonai Ulakpatian yang terdapat di Provinsi Riau. Kajian ini merupakan kajian linguistik tentang perubahan bunyi yang terjadi pada bunyi-bunyi berbeda menjadi sama, yang berada pada posisi antara dua vokal di tengah kata dalam sebuah isolek yang digunakan oleh suku Bonai di Desa Ulakpatian, Kabupaten Rokan Hulu. Data berupa tuturan masyarakat suku Bonai dikumpulkan dengan penerapan metode cakap dan metode simak dengan menggunakan teknik pancing dan teknik rekam. Analisis data dilakukan dengan pentranskripsian fonetis dengan simbol IPA, pembandingan data dengan leksikon PM, dan penarikan simpulan. Hasil penelitian menunjukkan bahwa isolek Bonai Ulakpatian memiliki empat bentuk asimilasi pada posisi antara dua vokal di tengah kata, yaitu 1) PM*nd/v-v> BU [n]/v-v, 2) PM*ŋg/v-v> BU [ŋ]/v-v, 3) PM*mb/v-v> BU [m]/v-v yang merupakan asimilasi progresif total dan asimilasi fonetis, dan 4) PM*nj/v-v> BU [ñ]/v-v yang merupakan asimilasi resiprokal dan fonemis.

A Hybrid Siamese Neural Network for Natural Language Inference in Cyber-Physical Systems

2021 ◽  
Vol 21 (2) ◽  
pp. 1-25
Author(s):  
Pin Ni ◽  
Yuming Li ◽  
Gangmin Li ◽  
Victor Chang
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Short Term Memory ◽  
Physical World ◽  
Heterogeneous Data ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Language Data ◽  
Text Language ◽  
Different Sources

Cyber-Physical Systems (CPS), as a multi-dimensional complex system that connects the physical world and the cyber world, has a strong demand for processing large amounts of heterogeneous data. These tasks also include Natural Language Inference (NLI) tasks based on text from different sources. However, the current research on natural language processing in CPS does not involve exploration in this field. Therefore, this study proposes a Siamese Network structure that combines Stacked Residual Long Short-Term Memory (bidirectional) with the Attention mechanism and Capsule Network for the NLI module in CPS, which is used to infer the relationship between text/language data from different sources. This model is mainly used to implement NLI tasks and conduct a detailed evaluation in three main NLI benchmarks as the basic semantic understanding module in CPS. Comparative experiments prove that the proposed method achieves competitive performance, has a certain generalization ability, and can balance the performance and the number of trained parameters.

scholarly journals Hippocampal Interneurons are Required for Trace Eyeblink Conditioning in Mice

2021 ◽  
Author(s):  
Wei-Wei Zhang ◽  
Rong-Rong Li ◽  
Jie Zhang ◽  
Jie Yan ◽  
Qian-Hui Zhang ◽  
...  
Keyword(s):  
Eyeblink Conditioning ◽  
Pyramidal Cells ◽  
Conditioned Eyeblink ◽  
Cellular Mechanisms ◽  
Sustained Activity ◽  
Early Acquisition ◽  
Freely Moving ◽  
Trace Eyeblink Conditioning

AbstractWhile the hippocampus has been implicated in supporting the association among time-separated events, the underlying cellular mechanisms have not been fully clarified. Here, we combined in vivo multi-channel recording and optogenetics to investigate the activity of hippocampal interneurons in freely-moving mice performing a trace eyeblink conditioning (tEBC) task. We found that the hippocampal interneurons exhibited conditioned stimulus (CS)-evoked sustained activity, which predicted the performance of conditioned eyeblink responses (CRs) in the early acquisition of the tEBC. Consistent with this, greater proportions of hippocampal pyramidal cells showed CS-evoked decreased activity in the early acquisition of the tEBC. Moreover, optogenetic suppression of the sustained activity in hippocampal interneurons severely impaired acquisition of the tEBC. In contrast, suppression of the sustained activity of hippocampal interneurons had no effect on the performance of well-learned CRs. Our findings highlight the role of hippocampal interneurons in the tEBC, and point to a potential cellular mechanism subserving associative learning.

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