Adjective Learning by Spanish-Speakers Children and Adults. The Impact of Morphology and Semantic Information

2020 ◽  
Vol 181 (2-3) ◽  
pp. 54-67
Author(s):  
Florencia Mareovich ◽  
Andrea S. Taverna ◽  
Olga A. Peralta
Keyword(s):  
Semantic Information ◽  
Spanish Speakers ◽  
The Impact

Infoveillance based on Social Sensors to Analyze the impact of Covid19 in South American Population (Preprint)

2020 ◽  
Author(s):  
Josimar E. Chire Saire
Keyword(s):  
Text Mining ◽  
Electronic Communication ◽  
Spanish Speakers ◽  
South American ◽  
South American Population ◽  
The People ◽  
Data Source ◽  
The Impact ◽  
General Concern ◽  
Social Sensors

BACKGROUND Infoveillance is an application from Infodemiology field with the aim to monitor public health and create public policies. Social sensor is the people providing thought, ideas through electronic communication channels(i.e. Internet). The actual scenario is related to tackle the covid19 impact over the world, many countries have the infrastructure, scientists to help the growth and countries took actions to decrease the impact. South American countries have a different context about Economy, Health and Research, so Infoveillance can be a useful tool to monitor and improve the decisions and be more strategical. The motivation of this work is analyze the capital of Spanish Speakers Countries in South America using a Text Mining Approach with Twitter as data source. The preliminary results helps to understand what happens two weeks ago and opens the analysis from different perspectives i.e. Economics, Social. OBJECTIVE Analyze the behaviour of South American Capitals in front of covid19 pandemics and show the helpfulness of Text Mining Approach for Infoveillance tasks. METHODS Text Mining process RESULTS - Argentina and Venezuela capitals are the biggest number of post during this period, opposite with Bolivia, Ecuador and Uruguay. - Most relevant users are related to mass media like radio, television or newspapers. - There is a general concern about covid19 but every country talks about different areas: Economics, Health, Environmental Impact. CONCLUSIONS Infoveillance based on Social Sensors with data coming from Twitter can help to understand the trends on the population of the capitals. Besides, it is necessary to filter the posts for processing the text and get insights about frequency, top users, most important terms. This data is useful to analyse the population from different approaches. INTERNATIONAL REGISTERED REPORT RR2-https://doi.org/10.1101/2020.04.06.20055749

scholarly journals Measures of speech rhythm and the role of corpus-based word frequency: a multifactorial comparison of Spanish(-English) speakers

2011 ◽  
Vol 11 (2) ◽  
pp. 1 ◽  
Author(s):  
Michael J. Harris ◽  
Stefan Th. Gries
Keyword(s):  
Word Frequency ◽  
Binary Logistic Regression ◽  
Spanish Speakers ◽  
English Speakers ◽  
Vowel Duration ◽  
Mexican Spanish ◽  
Speech Rhythm ◽  
Multiple Metrics ◽  
Main Effects ◽  
The Impact

In this study, we address various measures that have been employed to distinguish between syllable and stress- timed languages. This study differs from all previous ones by (i) exploring and comparing multiple metrics within a quantitative and multifactorial perspective and by (ii) also documenting the impact of corpus-based word frequency. We begin with the basic distinctions of speech rhythms, dealing with the differences between syllable-timed languages and stress-timed languages and several methods that have been used to attempt to distinguish between the two. We then describe how these metrics were used in the current study comparing the speech rhythms of Mexican Spanish speakers and bilingual English/Spanish speakers (speakers born to Mexican parents in California). More specifically, we evaluate how well various metrics of vowel duration variability as well as the so far understudied factor of corpus-based frequency allow to classify speakers as monolingual or bilingual. A binary logistic regression identifies several main effects and interactions. Most importantly, our results call the utility of a particular rhythm metric, the PVI, into question and indicate that corpus data in the form of lemma frequencies interact with two metrics of durational variability, suggesting that durational variability metrics should ideally be studied in conjunction with corpus-based frequency data.

scholarly journals Object Detection Based on Global-Local Saliency Constraint in Aerial Images

2020 ◽  
Vol 12 (9) ◽  
pp. 1435 ◽  
Author(s):  
Chengyuan Li ◽  
Bin Luo ◽  
Hailong Hong ◽  
Xin Su ◽  
Yajun Wang ◽  
...  
Keyword(s):  
Object Detection ◽  
Semantic Information ◽  
Feature Fusion ◽  
Aerial Images ◽  
Natural Image ◽  
Optical Remote Sensing ◽  
Complex Background ◽  
Bounding Boxes ◽  
The Impact ◽  
Oriented Bounding Boxes

Different from object detection in natural image, optical remote sensing object detection is a challenging task, due to the diverse meteorological conditions, complex background, varied orientations, scale variations, etc. In this paper, to address this issue, we propose a novel object detection network (the global-local saliency constraint network, GLS-Net) that can make full use of the global semantic information and achieve more accurate oriented bounding boxes. More precisely, to improve the quality of the region proposals and bounding boxes, we first propose a saliency pyramid which combines a saliency algorithm with a feature pyramid network, to reduce the impact of complex background. Based on the saliency pyramid, we then propose a global attention module branch to enhance the semantic connection between the target and the global scenario. A fast feature fusion strategy is also used to combine the local object information based on the saliency pyramid with the global semantic information optimized by the attention mechanism. Finally, we use an angle-sensitive intersection over union (IoU) method to obtain a more accurate five-parameter representation of the oriented bounding boxes. Experiments with a publicly available object detection dataset for aerial images demonstrate that the proposed GLS-Net achieves a state-of-the-art detection performance.

La influencia de "los de abajo" en tres procesos de cambio lingiiistico en el español de Morelia, Michoacán

1994 ◽  
Vol 18 (3) ◽  
pp. 257-269 ◽  
Author(s):  
Manuel J. Gutiérrez
Keyword(s):  
Formal Education ◽  
College Education ◽  
Spanish Speakers ◽  
Change Processes ◽  
Socioeconomic Group ◽  
Linguistic Change ◽  
Low Socioeconomic ◽  
The One ◽  
The Impact ◽  
Socioeconomic Levels

SUMMARY The Impact of "the Underdogs" in Three Processes of Linguistic Change in the Spanish of Morelia, Michoacán This paper deals with the role that the educational and the socioeconomic levels of the speakers play in some processes of linguistic change. Three phenomena of the Spanish grammar in different stages of linguistic change are examined in the light of the data collected among Spanish speakers from Morelia, Michoacan: (a) the opposition "periphrastic/morphological future," (b) the use of pluperfect subjunctive in the apodosis of conditional sentences instead of compound conditional, and (c) the innovative use of the copula estar. Results from the analysis reveal that in the two more advanced change processes (a and b), the lower educational levels and the low socioeconomic group are the leaders, while the group with more formal education and the middle-high socioeconomic group have joined, although with some resistance, the tendency marked by the leader groups. The analysis of the ser/estar opposition evidences an innovative use of the copula estar in the community. This change is in the first stages and consists of an extension of the estar semantic domain. The educational and socioeconomic levels also show differences in the use of this innovative form. Speakers with college education and speakers of the upper-middle socioeconomic group are more resistant to adopt the innovative use. However, speakers with less education and speakers of the low socioeconomic group show a very important proportion of the innovative use. The results found seem to suggest that the size of the group with less education and the size of the low socioeconomic group in communities like the one studied permit the imposition of some changes that are led by them. RESUMO La influo de la "subuloj " en tri procezoj de lingvosangigo en la hispana de Morelia en Michoacdn La artikolo temas pri la rolo de la eduka kaj sociekonomia niveloj de la parolantoj en procezoj de lingvosangigo. La aǔtoro studas tri fenomenojn de la hispana gramatiko en diversaj stadioj de lingvosangigo per faktoj observitaj inter parolantoj de la hispana en Morelia en Michoacán: (1) la alternativo inter helpverba kaj morfologia futuro, (2) la uzo de pluskvamperfekta subjunktivo en la cefpropozicio de kondicaj frazoj anstataǔ la helpverba kondicionalo, kaj (3) la novstila uzo de la kopulo estar. La rezultoj montras, ke en la du pli progresintaj ŝanĝoprocezoj (1 kaj 2), la malpli altaj edukniveloj kaj la malalta sociekonomia grupo gvidas, dum la grupo kun pli da formala edukigo kaj la mezalta sociekonomia grupo postsekvas, ec se kun iom da rezisto, la tendencon indikitan de la gvidantaj grupoj. La analizo de la alternativo ser/estar montras novstilan uzon de estar en la komunumo. Tiu ŝanĝo estas en la komenca stadio kaj konsistas el plivastigo de la signifo de estar. La niveloj kondutas malsame ankaǔ rilate al ĉi tiu novaĵo. Parolantoj kun altlerneja edukigo kaj tiuj el la mezalta sociekonomia grupo rezistas la disvastigon de tiu novstila uzo. Aliflanke parolantoj malpli edukitaj kaj sur malpli alta sociekonomia nivelo uzas la novstilaĵon grandkvante. La trovitaj rezultoj sajnas sugesti, ke pro sia grandeco la malaltaj socigrupoj kapablas en socio kiel la studita esti gvidantaj en sango.

scholarly journals Ekstraksi Informasi Semantik dan Spatiotemporal pada Artikel Online Terkait Bencana di Indonesia

2020 ◽  
Vol 10 (1) ◽  
pp. 114-121
Author(s):  
Ashr Hafiizh Tantri ◽  
Nur Aini Rakhmawati
Keyword(s):  
Natural Disasters ◽  
Information Structure ◽  
Semantic Information ◽  
Engineering Application ◽  
Extraction Process ◽  
Inference Process ◽  
Literature Study ◽  
Semantic Approach ◽  
Types Of Information ◽  
The Impact

Indonesia is one country that has a high risk of natural disasters. Ranked in 36 out of 172 countries in disaster index and having 2,372 disaster incidents in 2017, actions need to be taken to minimize the impact of natural disasters. One of it is to do a hazard map modeling. In making hazard maps, several approaches can be used, one of which is the semantic approach to extract disaster information. Therefore, this study aims to develop a system that can be used to extract spatiotemporal and semantic information related to natural disasters in Indonesia. This study uses the NLP method in conducting the information extraction process and  carried out using the GATE (General Architecture for Text Engineering) application. In processing Indonesian language articles, it is necessary to develop the plugin because the Indonesian information structure is different from the default information structure in GATE application. The plugin development process is done by using ontology as the basis for determining semantic information. Literature study was carried out related to government regulations that further explained the need for semantic and spatiotemporal information about disaster events. system performance developed produces a precision value of 38% and a recall value of 32%. this is because the system experiences some difficulties in carrying out the information inference process. The reason for low precision rate is because the rules used in the inference process to pair the three types of information still cannot accommodate the variation of information positions in different sentences.

scholarly journals 3D Semantic VSLAM of Indoor Environment Based on Mask Scoring RCNN

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chongben Tao ◽  
Yufeng Jin ◽  
Feng Cao ◽  
Zufeng Zhang ◽  
Chunguang Li ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Semantic Information ◽  
Moving Objects ◽  
Experimental Comparison ◽  
Indoor Environments ◽  
Feature Points ◽  
Current Frame ◽  
Semantic Map ◽  
Key Frame ◽  
The Impact

In view of existing Visual SLAM (VSLAM) algorithms when constructing semantic map of indoor environment, there are problems with low accuracy and low label classification accuracy when feature points are sparse. This paper proposed a 3D semantic VSLAM algorithm called BMASK-RCNN based on Mask Scoring RCNN. Firstly, feature points of images are extracted by Binary Robust Invariant Scalable Keypoints (BRISK) algorithm. Secondly, map points of reference key frame are projected to current frame for feature matching and pose estimation, and an inverse depth filter is used to estimate scene depth of created key frame to obtain camera pose changes. In order to achieve object detection and semantic segmentation for both static objects and dynamic objects in indoor environments and then construct dense 3D semantic map with VSLAM algorithm, a Mask Scoring RCNN is used to adjust its structure partially, where a TUM RGB-D SLAM dataset for transfer learning is employed. Semantic information of independent targets in scenes provides semantic information including categories, which not only provides high accuracy of localization but also realizes the probability update of semantic estimation by marking movable objects, thereby reducing the impact of moving objects on real-time mapping. Through simulation and actual experimental comparison with other three algorithms, results show the proposed algorithm has better robustness, and semantic information used in 3D semantic mapping can be accurately obtained.

The Influence of Semantic Context on the Perception of Spanish-Accented American English

2013 ◽  
Vol 56 (5) ◽  
pp. 1567-1578 ◽  
Author(s):  
Alison Behrman ◽  
Ali Akhund
Keyword(s):  
Semantic Information ◽  
American English ◽  
Semantic Category ◽  
Semantic Context ◽  
Spanish Speakers ◽  
Accented Speech ◽  
Main Effect ◽  
Dependent Variables ◽  
True False

Purpose In this article, the authors examine (a) the effect of semantic context on accentedness, comprehensibility, and intelligibility of Spanish-accented American English (AE) as judged by monolingual AE listeners and (b) the interaction of semantic context and accentedness on comprehensibility and intelligibility. Method Twenty adult native (L1) Spanish speakers proficient in AE and 4 L1 AE speakers (controls) read 48 statements consisting of true–false, semantically meaningful, and semantically anomalous sentences. Eighty monolingual AE listeners assessed accentedness, comprehensibility, and intelligibility of the statements. Results A significant main effect was found for semantic category on all 3 dependent variables. Accents were perceived to be stronger, and both comprehensibility and intelligibility were worse, in semantically anomalous contexts. Speaker data were grouped into strong, mid-level, and mild accents. The interaction between semantic category and accent was significant for both comprehensibility and intelligibility. The effect of semantic context was strongest for strong accents. Intelligibility was excellent for speakers with mid-level accents in true–false and semantically meaningful contexts, and it was excellent for mild accents in all contexts. Conclusions Listeners access semantic information, in addition to phonetic and phonotactic features, in the perception of nonnative speech. Both accent level and semantic context are important in research on foreign-accented speech.

scholarly journals Three-Dimensional Model of the Moon with Semantic Information of Craters Based on Chang’e Data

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 959
Author(s):  
Yunfan Lu ◽  
Yifan Hu ◽  
Jun Xiao ◽  
Lupeng Liu ◽  
Long Zhang ◽  
...  
Keyword(s):  
Reference Frame ◽  
3D Model ◽  
Semantic Information ◽  
Three Dimensional ◽  
Impact Craters ◽  
Detection Methods ◽  
The Moon ◽  
Three Dimensional Model ◽  
Data Set ◽  
The Impact

China’s Chang’e lunar exploration project obtains digital orthophoto image (DOM) and digital elevation model (DEM) data covering the whole Moon, which are critical to lunar research. The DOM data have three resolutions (i.e., 7, 20 and 50 m), while the DEM has two resolutions (i.e., 20 and 50 m). Analysis and research on these image data effectively help humans to understand the Moon. In addition, impact craters are considered the most basic feature of the Moon’s surface. Statistics regarding the size and distribution of impact craters are essential for lunar geology. In existing works, however, the lunar surface has been reconstructed less accurately, and there is insufficient semantic information regarding the craters. In order to build a three-dimensional (3D) model of the Moon with crater information using Chang‘e data in the Chang‘e reference frame, we propose a four-step framework. First, software is implemented to annotate the lunar impact craters from Chang’e data by complying with our existing study on an auxiliary annotation method and open-source software LabelMe. Second, auxiliary annotation software is adopted to annotate six segments in the Chang’e data for an overall 25,250 impact crater targets. The existing but inaccurate craters are combined with our labeled data to generate a larger dataset of craters. This data set is analyzed and compared with the common detection data. Third, deep learning detection methods are employed to detect impact craters. To address the problem attributed to the resolution of Chang’e data being too high, a quadtree decomposition is conducted. Lastly, a geographic information system is used to map the DEM data to 3D space and annotate the semantic information of the impact craters. In brief, a 3D model of the Moon with crater information is implemented based on Chang’e data in the Chang‘e reference frame, which is of high significance.

scholarly journals Relationships as regulators of discourse interaction in Spanish

2019 ◽  
Vol 79 ◽  
pp. 297-322
Author(s):  
Magdalena Romera
Keyword(s):  
Basic Principle ◽  
Spanish Speakers ◽  
Strong Disagreement ◽  
Different Types ◽  
Points Of View ◽  
Cultural Code ◽  
Linguistic Behavior ◽  
The Impact ◽  
The Relationship ◽  
Strong Relationships

In this paper we argue that in analyses of discourse interaction the relationship between participants must be considered as a parameter that conditions their linguistic behavior. A relationship is the result of the experiences shared by partners which create a “cultural code” between them. Each relationship brings a set of circumstances into play that regulates how members behave and how they interpret each other’s words and actions. Our proposal stems from observing how Spanish speakers who hold different types of relationships handle opposing points of view in conversation. Our results show that the expression and interpretation of dissent is linked to the interlocutors’ need to maintain the relationship in good terms. In order to protect relationships, the basic principle guiding interaction is to reach consensus. Additionally, the type and strength of the relationship condition the impact of expressions. Strong disagreement is allowed in strong relationships, as the risk for its affecting the relationship is low. Conversely, weak disagreement is preferred in weak relationships, since opposing views may result in higher impact.

scholarly journals Robust Loop Closure Detection Integrating Visual–Spatial–Semantic Information via Topological Graphs and CNN Features

2020 ◽  
Vol 12 (23) ◽  
pp. 3890
Author(s):  
Yuwei Wang ◽  
Yuanying Qiu ◽  
Peitao Cheng ◽  
Xuechao Duan
Keyword(s):  
Semantic Information ◽  
Graph Matching ◽  
Spatial Relationships ◽  
Dynamic Scenes ◽  
Topological Graphs ◽  
Loop Closure ◽  
Loop Closure Detection ◽  
Visual Spatial ◽  
Localization And Mapping ◽  
The Impact

Loop closure detection is a key module for visual simultaneous localization and mapping (SLAM). Most previous methods for this module have not made full use of the information provided by images, i.e., they have only used the visual appearance or have only considered the spatial relationships of landmarks; the visual, spatial and semantic information have not been fully integrated. In this paper, a robust loop closure detection approach integrating visual–spatial–semantic information is proposed by employing topological graphs and convolutional neural network (CNN) features. Firstly, to reduce mismatches under different viewpoints, semantic topological graphs are introduced to encode the spatial relationships of landmarks, and random walk descriptors are employed to characterize the topological graphs for graph matching. Secondly, dynamic landmarks are eliminated by using semantic information, and distinctive landmarks are selected for loop closure detection, thus alleviating the impact of dynamic scenes. Finally, to ease the effect of appearance changes, the appearance-invariant descriptor of the landmark region is extracted by a pre-trained CNN without the specially designed manual features. The proposed approach weakens the influence of viewpoint changes and dynamic scenes, and extensive experiments conducted on open datasets and a mobile robot demonstrated that the proposed method has more satisfactory performance compared to state-of-the-art methods.

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