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Sentence-final completion tasks serve as valuable tools in studying language processing and the associated predictive mechanisms. There are several established sentence-completion norms for languages like English, Portuguese, French, and Spanish, each tailored to the language it was designed for and evaluated in. Yet, cultural variations among native speakers of the same language complicate the claim of a universal application of these norms. In this study, we developed a corpus of 2925 sentence-completion norms specifically for Mexican Spanish. This corpus is distinctive for several reasons: Firstly, it is the most comprehensive set of sentence-completion norms for Mexican Spanish to date. Secondly, it offers a substantial range of experimental stimuli with considerable variability in terms of the predictability of word sentence completion (cloze probability/surprisal) and the level of uncertainty inherent in the sentence context (entropy). Thirdly, the syntactic complexity of the sentences in the corpus is varied, as are the characteristics of the final word nouns (including aspects of concreteness/abstractness, length, and frequency). This paper details the generation of the sentence contexts, explains the methodology employed for data collection from a total of 1470 participants, and outlines the approach to data analysis for the establishment of sentence-completion norms. These norms provide a significant contribution to fields such as linguistics, cognitive science, and machine learning, among others, by enhancing our understanding of language, predictive mechanisms, knowledge representation, and context representation. The collected data is accessible through the Open Science Framework (OSF) at the following link: https://osf.io/js359/?view_only=bb1b328d37d643df903ed69bb2405ac0. [ABSTRACT FROM AUTHOR]

As the bilingual Spanish-speaking population in the United States (U.S.) steadily rises (U.S. Census Bureau in Language spoken at home, https://data.census.gov/cedsci/profile?q=United%20States&g=0100000US, 2020), the need for systemic therapists who are competent in working with Spanish-speaking clients also increases. While it is unrealistic to require all mental health practitioners to be bilingual English and Spanish speakers, systemic therapists can improve their understanding of the impact that clients' native language can have on the therapeutic process. In this paper, we synthesize concepts from narrative therapy and linguistic relativity to provide non-Spanish-speaking clinicians with a unique perspective of case conceptualizations and therapeutic interventions for clients who natively speak Spanish. A clinical vignette is presented to illustrate the practical application of linguistic relativity informed systemic therapy. Potential theoretical and clinical implications of this treatment suggestion are explored. [ABSTRACT FROM AUTHOR]

The present paper aims to describe the process of creating CHARG—Corpus de Habla Radiofónica de Guayaquil (the Guayaquil Radiophonic Speech Corpus). It is the first systematized spoken corpus for this rather under-researched variety of Spanish. Guayaquil is the most populated city of Ecuador, while its capital city is Quito. Therefore, Ecuador is a rare case of a Spanish-speaking country with two major urban centers that belong to two separate dialectal zones, offering a very peculiar sociolinguistic context. CHARG is a corpus composed of Guayaquil radio programs. Its structure is organized by non-linguistic criteria (program type) in order to ensure a representative and balanced sample. The paper describes the design of the corpus (defining the study population, sample and stratification) and its construction (recording procedure, speakers and speech style coding, transcription and annotation). As a result, CHARG consists of 24 h of transcriptions and annotations of recordings from 142 speakers. The paper's potential use is twofold: since it presents a step-by-step procedure of corpus construction that can be replicated, the readers might be interested in both the procedure and the corpus itself as a research material. [ABSTRACT FROM AUTHOR]

A sign language recognition system can be applied to reduce a communication gap between deaf and normal persons. However, the Indian sign language recognition (ISL) systems are in the developing stage. Most of the recent ISL recognition systems use convolutional neural networks (CNNs) where applied convolution operation shifts a kernel to overlapping portions over the image. However, these kernels may learn redundant data since real-world images have very high correlations. The training process of neural networks is challenging for redundant image data. To overcome this limitation, an ISL recognition system has been proposed in this paper that uses the network deconvolution technique. This technique reduces not only pixel-wise correlation but also a channel-wise correlation in images. The proposed model is also augmented with a spatial transformer network to increase spatial invariance of convolution operations against spatial transformations. The proposed recognizer offers better accuracy most of the time than other experimented systems on two ISL datasets VUCS_ISL_I and created VUCS_ISL_II and standard datasets of other sign languages, i.e., American sign language, Arabic sign language, Spanish sign language. [ABSTRACT FROM AUTHOR]

The widespread availability of scientific documents in multiple languages, coupled with the development of automatic translation and editing tools, has created a demand for efficient methods that can detect plagiarism across different languages. In this paper, we present a novel cross-lingual plagiarism detection approach. The algorithm is based on the merger of two existing approaches that in turn achieve state-of-the-art (SOTA) or comparable to SOTA results on different benchmarks. The detailed analysis stages of existing approaches were sequentially merged levelling out the disadvantages of the approaches. The obtained algorithm significantly outperforms the ones it was merged of surpassing them by from 23 to 33% Plagdet Score, depending on different language pairs. The comparison between observed approaches was evaluated on a newly generated multilingual (English, Russian, Spanish, Armenian) test collection, where each suspicious document could contain plagiarised fragments from several languages. The merged method is applicable to various under-resourced languages which is shown on the example of the Armenian language. [ABSTRACT FROM AUTHOR]

This paper introduces a system that incorporates several strategies based on scientific models of how the brain records and recovers memories. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architecture that can be adapted to any language. A special case is studied and tested regarding the Spanish language. The applications of this proposal are vast because, in general, information such as text way, reports, emails, and web content, among others, is considered unstructured and, hence, the repositories based on SQL databases usually do not handle this kind of data correctly and efficiently. The conversion of unstructured textual information to structured one can be useful in contexts such as Natural Language Generation, Data Mining, and dynamic generation of theories, among others. [ABSTRACT FROM AUTHOR]

In this paper, we highlight the importance of distilling the computational assessments of constructed responses to validate the indicators/proxies of constructs/trins using an empirical illustration in automated summary evaluation. We present the validation of the Inbuilt Rubric (IR) method that maps rubrics into vector spaces for concepts' assessment. Specifically, we improved and validated its scores' performance using latent variables, a common approach in psychometrics. We also validated a new hierarchical vector space, namely a bifactor IR. 205 Spanish undergraduate students produced 615 summaries of three different texts that were evaluated by human raters and different versions of the IR method using latent semantic analysis (LSA). The computational scores were validated using multiple linear regressions and different latent variable models like CFAs or SEMs. Convergent and discriminant validity was found for the IR scores using human rater scores as validity criteria. While this study was conducted in the Spanish language, the proposed scheme is language-independent and applicable to any language. We highlight four main conclusions: (1) Accurate performance can be observed in topic-detection tasks without hundreds/thousands of pre-scored samples required in supervised models. (2) Convergent/discriminant validity can be improved using measurement models for computational scores as they adjust for measurement errors. (3) Nouns embedded in fragments of instructional text can be an affordable alternative to use the IR method. (4) Hierarchical models, like the bifactor IR, can increase the validity of computational assessments evaluating general and specific knowledge in vector space models. R code is provided to apply the classic and bifactor IR method. [ABSTRACT FROM AUTHOR]

In this paper, a public dataset for Offline Handwriting Recognition, along with an appropriate evaluation method to provide benchmark indicators at sentence level, is presented. This dataset, called SPA-Sentences, consists of offline handwritten Spanish sentences extracted from 1617 forms produced by the same number of writers. A total of 13,691 sentences comprising around 100,000 word instances out of a vocabulary of 3288 words occur in the collection. Careful attention has been paid to make the baseline experiments both reproducible and competitive. To this end, experiments are based on state-of-the-art recognition techniques combining convolutional blocks with one-dimensional Bidirectional Long Short Term Memory (LSTM) networks using Connectionist Temporal Classification (CTC) decoding. The scripts with the entire experimental setting have been made available. The SPA-Sentences dataset and its baseline evaluation are freely available for research purposes via the institutional University repository. We expect the research community to include this corpus, as is usually done with English IAM and French RIMES datasets, in their battery of experiments when reporting novel handwriting recognition techniques. [ABSTRACT FROM AUTHOR]

This paper introduces MadSex, a spoken corpus of 54 sociolinguistic interviews in Spanish based on the topic of sexuality. It was collected in order to study the cognitive sociolinguistic variation of sexual concepts. The paper presents and justifies methodological decisions taken during design, collection and transcription stages. Informants were selected in Madrid, based on a pre-stratified sample divided by sex, age and level of education. The interview methodology relied on an opinion questionnaire designed for the indirect elicitation of sexual concepts, which overcame successfully the limitations imposed by the low frequencies of semantic variables in discourse and the impact of sexual taboo in interaction. Relevant aspects of fieldwork, empathy and ethical protocols are also detailed in the paper. Transcription and markup are explained. Finally, an overview of the corpus is given, as well as some research papers based on it. Examples of the questionnaire are also provided. [ABSTRACT FROM AUTHOR]

Gender bias is affecting many natural language processing applications. While we are still far from proposing debiasing methods that will solve the problem, we are making progress analyzing the impact of this bias in current algorithms. This paper provides an extensive study of the underlying gender bias in popular contextualized word embeddings. Our study provides an insightful analysis of evaluation measures applied to several English data domains and the layers of the contextualized word embeddings. It is also adapted and extended to the Spanish language. Our study points out the advantages and limitations of the various evaluation measures that we are using and aims to standardize the evaluation of gender bias in contextualized word embeddings. [ABSTRACT FROM AUTHOR]

This paper describes a support vector machine-based approach to different tasks related to sentiment analysis in Twitter for Spanish. We focus on parameter optimization of the models and the combination of several models by means of voting techniques. We evaluate the proposed approach in all the tasks that were defined in the five editions of the TASS workshop, between 2012 and 2016. TASS has become a framework for sentiment analysis tasks that are focused on the Spanish language. We describe our participation in this competition and the results achieved, and then we provide an analysis of and comparison with the best approaches of the teams who participated in all the tasks defined in the TASS workshops. To our knowledge, our results exceed those published to date in the sentiment analysis tasks of the TASS workshops. [ABSTRACT FROM AUTHOR]

In this paper, we present SFU ReviewSP-NEG, the first Spanish corpus annotated with negation with a wide coverage freely available. We describe the methodology applied in the annotation of the corpus including the tagset, the linguistic criteria and the inter-annotator agreement tests. We also include a complete typology of negation patterns in Spanish. This typology has the advantage that it is easy to express in terms of a tagset for corpus annotation: the types are clearly defined, which avoids ambiguity in the annotation process, and they provide wide coverage (i.e. they resolved all the cases occurring in the corpus). We use the SFU ReviewSP as a base in order to make the annotations. The corpus consists of 400 reviews, 221,866 words and 9455 sentences, out of which 3022 sentences contain at least one negation structure. [ABSTRACT FROM AUTHOR]

This paper describes the design, development and field evaluation of a machine translation system from Spanish to Spanish Sign Language (LSE: Lengua de Signos Española). The developed system focuses on helping Deaf people when they want to renew their Driver's License. The system is made up of a speech recognizer (for decoding the spoken utterance into a word sequence), a natural language translator (for converting a word sequence into a sequence of signs belonging to the sign language), and a 3D avatar animation module (for playing back the signs). For the natural language translator, three technological approaches have been implemented and evaluated: an example-based strategy, a rule-based translation method and a statistical translator. For the final version, the implemented language translator combines all the alternatives into a hierarchical structure. This paper includes a detailed description of the field evaluation. This evaluation was carried out in the Local Traffic Office in Toledo involving real government employees and Deaf people. The evaluation includes objective measurements from the system and subjective information from questionnaires. The paper details the main problems found and a discussion on how to solve them (some of them specific for LSE). [ABSTRACT FROM AUTHOR]

This paper reports the work for the EnConversion of input Punjabi sentences to an interlingua representation called Universal Networking Language (UNL). The UNL system consists of two main components, namely, EnConverter (used for converting the text from a source language to UNL) and DeConverter (used for converting the text from UNL to a target language). This paper discusses the framework for designing the EnConverter for Punjabi language with a special focus on generation of UNL attributes and relations from Punjabi source text. It also describes the working of Punjabi Shallow Parser used for the processing of the input sentence, which performs the tasks of Tokenizer, Morph-analyzer, Part-of-Speech Tagger and Chunker. This paper also considers the seven phases used in the process of EnConversion of input Punjabi text to UNL representation. The paper highlights the EnConversion analysis rules used for the EnConverter and indicates its usage in the generation of UNL expressions. This paper also covers the results of implementation of Punjabi EnConverter and its evaluation on sample UNL sentences available at Spanish Language Server. The accuracy of the developed system has also been presented in this paper. [ABSTRACT FROM AUTHOR]

Interactive Voice Response (IVR), an automated system that administers surveys over the phone, is a potentially important technology for mental health services research. Although a number of studies have compared IVR to live interviews, few have looked at IVR in comparison to pencil-and-paper survey administration. Further, few studies have included subjects from those populations most likely to benefit from IVR technology, namely patients with lower education levels and non-English-speaking patients. This randomized clinical study, conducted at a community health center serving low-income English- and Spanish-speaking populations, assessed the reliability of an IVR-administered Brief Symptom Inventory (BSI) relative to a paper-and-pencil version. The study was adequately powered. Results showed that patients gave similar responses to the IVR and paper-and-pencil surveys; in addition, patients were generally equally satisfied with both experiences. We conclude that, while more large-scale research is needed, IVR can be a useful survey administration tool. [ABSTRACT FROM AUTHOR]

Our objective was to perform translation, cross-cultural adaptation and validation of the sino-nasal outcome test 22 (SNOT-22) to Spanish language. SNOT-22 was translated, back translated, and a pretest trial was performed. The study included 119 individuals divided into 60 cases, who met diagnostic criteria for chronic rhinosinusitis according to the European Position Paper on Rhinosinusitis 2012; and 59 controls, who reported no sino-nasal disease. Internal consistency was evaluated with Cronbach's alpha test, reproducibility with Kappa coefficient, reliability with intraclass correlation coefficient (ICC), validity with Mann-Whitney U test and responsiveness with Wilcoxon test. In cases, Cronbach's alpha was 0.91 both before and after treatment, as for controls, it was 0.90 at their first test assessment and 0.88 at 3 weeks. Kappa coefficient was calculated for each item, with an average score of 0.69. ICC was also performed for each item, with a score of 0.87 in the overall score and an average among all items of 0.71. Median score for cases was 47, and 2 for controls, finding the difference to be highly significant (Mann-Whitney U test, p < 0.001). Clinical changes were observed among treated patients, with a median score of 47 and 13.5 before and after treatment, respectively (Wilcoxon test, p < 0.001). The effect size resulted in 0.14 in treated patients whose status at 3 weeks was unvarying; 1.03 in those who were better and 1.89 for much better group. All controls were unvarying with an effect size of 0.05. The Spanish version of the SNOT-22 has the internal consistency, reliability, reproducibility, validity and responsiveness necessary to be a valid instrument to be used in clinical practice. [ABSTRACT FROM AUTHOR]

This paper presents results of a study on teachers' conceptions of assessment carried out on a sample of 493 teachers of Spanish as foreign language from all over the world. At the moment of data collection, the participants were members of an international online teacher community and were teaching at different professional contexts: basic compulsory school, and diverse extra-school teaching contexts, such as language academies and in-company education services. A self-report questionnaire was presented online to the teachers with 40 rating items capturing their conceptions of assessment and habitual assessment practices. Confirmatory factor analysis was undertaken to evaluate the theoretical model. Results reveal a new bifactor model of conceptions of assessment, which contrasts with the prevailing literature in the field. More specifically, results point to differences in teachers' conceptions of assessment depending on four aspects: how assessment affects the teaching process, the learning process, the certification of learning results, and the participants' accountability to different audiences, such as colleague teachers, families, and the general society. Our results further put forward that the learner population, whether children-adolescents or adults, influences teachers' conceptions of assessment. This should lead researchers and practitioners to rethink teachers' conceptions of assessment in a broader context than has been considered to date. [ABSTRACT FROM AUTHOR]

Explaining why the same passage may have different rhetorical structures when conveyed in different languages remains an open question. Starting from a trilingual translation corpus, this paper aims to provide a new qualitative method for the comparison of rhetorical structures in different languages and to specify why translated texts may differ in their rhetorical structures. To achieve these aims we have carried out a contrastive analysis, comparing a corpus of parallel English, Spanish and Basque texts, using Rhetorical Structure Theory. We propose a method to describe the main linguistic differences among the rhetorical structures of the three languages in the two annotation stages (segmentation and rhetorical analysis). We show a new type of comparison that has important advantages with regard to the quantitative method usually employed: it provides an accurate measurement of inter-annotator agreement, and it pinpoints sources of disagreement among annotators. With the use of this new method, we show how translation strategies affect discourse structure. [ABSTRACT FROM AUTHOR]

This paper presents the IULA Spanish LSP Treebank, an open-source treebank of over 40,000 sentences, developed in the framework of the European project METANET4U. The IULA Spanish LSP Treebank is the first technical corpus of Spanish annotated at surface syntactic level, following the dependency grammar theory. We present the method we used to create the resource and the linguistic annotations that the treebank provides, using examples and comparing with similar resources. We also provide the statistics of the treebank and the evaluation results. [ABSTRACT FROM AUTHOR]

In this paper we present the development of a text simplification system for Spanish. Text simplification is the adaptation of a text for the special needs of certain groups of readers, such as language learners, people with cognitive difficulties, and elderly people, among others. There is a clear need for simplified texts, but manual production and adaptation of existing text is labour-intensive and costly. Automatic simplification is a field which attracts growing attention in Natural Language Processing, but, to the best of our knowledge, there are no existing simplification tools for Spanish. We present a corpus study which aims to identify the operations a text simplification system needs to carry out in order to produce an output similar to what human editors produce when they simplify news texts. We also present a first prototype for automatic simplification, which shows that the most important simplification operations can be successfully treated. [ABSTRACT FROM AUTHOR]

Literature review on prosody reveals the lack of corpora for prosodic studies in Catalan and Spanish. In this paper, we present a corpus intended to fill this gap. The corpus comprises two distinct data-sets, a news subcorpus and a dialogue subcorpus, the latter containing either conversational or task-oriented speech. More than 25 h were recorded by twenty eight speakers per language. Among these speakers, eight were professional (four radio news broadcasters and four advertising actors). The entire material presented here has been transcribed, aligned with the acoustic signal and prosodically annotated. Two major objectives have guided the design of this project: (i) to offer a wide coverage of representative real-life communicative situations which allow for the characterization of prosody in these two languages; and (ii) to conduct research studies which enable us to contrast the speakers different speaking styles and discursive practices. All material contained in the corpus is provided under a Creative Commons Attribution 3.0 Unported License. [ABSTRACT FROM AUTHOR]

The impact-es diachronic corpus of historical Spanish compiles over one hundred books—containing approximately 8 million words—in addition to a complementary lexicon which links more than 10,000 lemmas with attestations of the different variants found in the documents. This textual corpus and the accompanying lexicon have been released under an open license (Creative Commons by-nc-sa) in order to permit their intensive exploitation in linguistic research. Approximately 7 % of the words in the corpus (a selection aimed at enhancing the coverage of the most frequent word forms) have been annotated with their lemma, part of speech, and modern equivalent. This paper describes the annotation criteria followed and the standards, based on the Text Encoding Initiative recommendations, used to represent the texts in digital form. [ABSTRACT FROM AUTHOR]

This paper will focus on recent and near-term future developments at FrameNet (FN) and the interoperability issues they raise. We begin by discussing the current state of the Berkeley FN database including major changes in the data format for the latest data release. We then briefly review two recent local projects, "Rapid Vanguarding', which has created a new interface for the frame and lexical unit definition process based on the Word Sketch Engine of Kilgarriff et al. (), and 'Beyond the Core', which has developed tools for annotating constructions, and created a sample 'construction' of especially 'interesting' constructions which are neither simply lexical nor easy for the standard parsers to parse. We also cover two current collaborations, FN's part in the development of the manually annotated subcorpus of the American National Corpus, and a pilot study on aligning WordNet and FrameNet, to exploit the complementary strengths of these quite different resources. We discuss FN-related research on Spanish, Japanese, German (SALSA), Chinese and other languages, and the language-independence of frames, along with interesting FN-related work by others, and a sketch of a large group of image-schematic frames which are now being added to FN. We close with some ideas about how FrameNet can be opened up, to allow broader participation in the development process without losing precision and coherence, including a small-scale study on acquiring data for FN using Amazon's Mechanical Turk crowd-sourcing system. [ABSTRACT FROM AUTHOR]

In this paper the transcription and evaluation of the corpus DIMEx100 for Mexican Spanish is presented. First we describe the corpus and explain the linguistic and computational motivation for its design and collection process; then, the phonetic antecedents and the alphabet adopted for the transcription task are presented; the corpus has been transcribed at three different granularity levels, which are also specified in detail. The corpus statistics for each transcription level are also presented. A set of phonetic rules describing phonetic context observed empirically in spontaneous conversation is also validated with the transcription. The corpus has been used for the construction of acoustic models and a phonetic dictionary for the construction of a speech recognition system. Initial performance results suggest that the data can be used to train good quality acoustic models. [ABSTRACT FROM AUTHOR]

Most current methods for automatic text categorization are based on supervised learning techniques and, therefore, they face the problem of requiring a great number of training instances to construct an accurate classifier. In order to tackle this problem, this paper proposes a new semi-supervised method for text categorization, which considers the automatic extraction of unlabeled examples from the Web and the application of an enriched self-training approach for the construction of the classifier. This method, even though language independent, is more pertinent for scenarios where large sets of labeled resources do not exist. That, for instance, could be the case of several application domains in different non-English languages such as Spanish. The experimental evaluation of the method was carried out in three different tasks and in two different languages. The achieved results demonstrate the applicability and usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, I measure the contribution of knowing Catalan to finding a job in Catalonia. In the early 1980s, a drastic language policy change ( normalització) promoted the learning and use of Catalan in Catalonia and managed to reverse the falling trend of its relative use vs Castilian (Spanish). Using census data for 1991 and 1996, I estimate a significant positive Catalan premium: the probability of being employed increases between 3 and 5 percentage points if individuals know how to read and speak Catalan; it increases between 2 and 6 percentage points for writing Catalan. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide guidelines for building a word alignment evaluation scheme. The notion of word alignment quality depends on the application: here we review standard scoring metrics for full text alignment and give explanations on how to use them better. We discuss strategies to build a reference corpus, and show that the ratio between ambiguous and unambiguous links in the reference has a great impact on scores measured with these metrics. In particular, automatically computed alignments with higher precision or higher recall can be favoured depending on the value of this ratio. Finally, we suggest a strategy to build a reference corpus particularly adapted to applications where recall plays a significant role, like in machine translation. The manually aligned corpus we built for the Spanish-English European Parliament corpus is also described. This corpus is freely available. [ABSTRACT FROM AUTHOR]

This paper describes a methodology aimed at grouping Catalan verbs according to their syntactic behavior. Our goal is to acquire a small number of basic classes with a high level of accuracy, using minimal resources. Information on syntactic class, expensive and slow to compile by hand, is useful for any NLP task requiring specific lexical information. We show that it is possible to acquire this kind of information using only a POS-tagged corpus. We perform two clustering experiments. The first one aims at classifying verbs into transitive, intransitive and verbs alternating with a se-construction. Our system achieves an average 0.84 F-score, for a task with a 0.33 baseline. The second experiment aims at further distinguishing among pure intransitives and verbs bearing a prepositional object. The baseline for the task is 0.51 and the upperbound 0.98. The system achieves an average 0.88 F-score. [ABSTRACT FROM AUTHOR]