Search Results (26)

Integrating people with hearing disabilities into schools is one of the biggest problems that Latin American societies face. Mexican Sign Language (MSL) is the main language and culture of the deaf community in Mexico. However, its use in formal education is still limited by structural inequalities, a lack of qualified interpreters, and a lack of technology that can support personalized instruction. This study outlines the conceptualization and development of a mobile application designed as an adaptive assistive technology for learning MSL, utilizing a combination of computer vision techniques, deep learning algorithms, and personalized pedagogical interaction. The suggested system uses convolutional neural networks (CNNs) and pose-estimation models to recognize hand gestures in real time with 95.7% accuracy. It then gives the learner instant feedback by changing the difficulty level. A dynamic learning engine automatically changes the level of difficulty based on how well the learner is doing, which helps them learn signs and phrases over time. The Scrum agile methodology was used during the development process. This meant that educators, linguists, and members of the deaf community all worked together to design the product. Early tests show that sign recognition accuracy and indicators of user engagement and motivation show favorable performance and are at appropriate levels. This proposal aims to enhance inclusive digital ecosystems and foster linguistic equity in Mexican education through scalable, mobile, and culturally relevant technologies, in addition to its technical contributions. Full article

Background: The American Society of Clinical Oncology (ASCO) established recommendations for palliative care (PC), and they still remain the most trusted source overall. The standard published by C. Earle (defined in solid tumors) for referral to PC is > 55%. However, these rates remain unclear in general onco-hematology. Our referral rate reaches 60%; while it meets the standard, there are significant differences between ST and HM. Several authors have already pointed out these discrepancies. Arguing in some cases its possible relationship with the different behavior of professionals with different pathologies. Objective: The primary objective of this work is to understand the role that PC plays in onco-hematology and to determine the profile of patients referred to PC. Therefore, the article aims to establish some recommendations related to the results of prevalent characteristics. Methods: The Mortality Subcommittee (MS) includes and registers in a database all cancer patients who died in hospital undergoing systemic anticancer therapy (SACT) in their last 30 days of life (SACT ≤ 30 d). PC, in turn, works on relieving symptoms related to the disease and the patient. To understand the impact of PC in the MS database patients, we reviewed the literature for symptoms related to palliative care activity. Subsequently, we selected some signs and symptoms, by consensus with our PC specialists, in order to add them to the MS database and register them retrospectively. We measured the percentage of patients who registered these symptoms based on the data found in their electronic records. The results include the comparison by group: between patients referred or not to the PC program (PCP), and between the pathologies ST and HM. We used the programming language R (version 4.2) in our statistical analysis, including the “compareGroups” package (version 4.6), applying the pertinent tests based on the distribution of the data. Results: We completed the records on the 1681 patients from the period 2020–2023. 59.4% were men, the average age was 65.5 years, and 73.5% had ST and 26.5% had HM. Patients with lung cancer predominate (28.5%), with 71% of them being in the stage IV, followed by leukemia (9.76%). 60% are in progression of their disease, and 77% have advanced disease (AD). The average therapeutic aggressiveness indicators were SACT < 30 d: 38.9% (ST: 33.4%; HM: 70.97%); SACT < 14 d: 16.36% (ST: 13.76%; HM: 31.56%); the change in therapeutic regimen was 22% (ST: 20.8%; HM: 25.1%). The referral rate to PCP was 59.7% (ST: 68.2% and HM: 36.3%). Late referral (PCP ≤3 days before death) occurred in 29.2% of all patients, being 29% for ST cases and 30.4% for HM cases. Regarding the recording of signs and symptoms: psycho-emotional and analgesia regimens (including opioids) are better recorded in the PCP group (p < 0.001); the more physical symptoms (dyspnea, bleeding, infections, and severe symptoms) do not present statistically significant differences, although the severe symptoms in the PCP group are more disabling (cerebral involvement, spinal cord compression, vertebral crushing). The number of bags of blood products transfused is significantly lower in the PCP group (average 6.9 vs. 12.7). The total number of symptom variables with significant statistical differences was 13 for ST and 8 for HM. Conclusions: In this cohort, patients visited by PC had a better record of psycho-emotional symptoms. We consider that patients who are in any of the following situations should be referred to PC: initial diagnosis of stage IV lung cancer, leukemia; patients with advanced disease; presence of pain requiring opioids; psychoemotional symptoms; need for >7 to 15 transfusions of blood products and, if there are disabling symptoms. PC improves professional interest in the psycho-emotional and fragility situation of these patients. According to our data (in terms of the number of variables with significant differences by pathology group), we observed that hematologists tend to take on palliative tasks more frequently than their oncologist peers, who delegate them to PC in order to have more time dedicated to their specific field. Full article

The transition to a circular economy depends on the widespread adoption of sustainable products by consumers. However, the point-of-sale purchase decision is a complex process, influenced not only by ethical arguments but also by sensory cues. This study investigates how the aesthetics (visual design) and materiality (tactile sensation) of green products shape value perception and purchase intention. Using a qualitative methodology based on a focus group, the research directly compares consumer reactions to green products (e.g., a bamboo toothbrush) versus their conventional alternatives (e.g., plastic). Thematic analysis of the data reveals a fundamental dichotomy among consumers: while one segment associates high-tech aesthetics and perfect finishes with quality and hygiene, another segment values natural materials and their “imperfections” as signs of authenticity and responsibility. The results demonstrate that there is no single, universally accepted “sustainable aesthetic” and highlight the need for designers and marketers to align the visual and tactile language of products with the value system of the target consumer segment. The study provides a framework for understanding how design can act as either a barrier to or a catalyst for the adoption of sustainable products. Full article

Late bilingual speakers immersed in a second language (L2) environment often experience the non-pathological attrition of their first language (L1), exhibiting selective and reversible changes in L1 processing and production. While attrition research has largely focused on long-term residents in anglophone countries, examining changes primarily within a single L1 domain, the present study employs a novel experimental design to investigate L1 attrition, alongside L2 acquisition, across three domains (i.e., the lexicon, syntax–pragmatics interface, and prosody) in two groups of L1-English L2-Italian late bilinguals: long-term residents in Italy vs. university students in the UK. A total of 112 participants completed online tasks assessing lexical retrieval, anaphora resolution, and sentence stress patterns in both languages. First, both bilingual groups showed comparable levels of semantic interference in lexical retrieval. Second, at the syntax–pragmatics interface, only residents in Italy showed signs of L1 attrition in real-time processing of anaphora, while resolution preferences were similar between groups; in the L2, both bilingual groups demonstrated target-like preferences, despite some slowdown in processing. Third, while both groups showed some evidence of target-like L2 prosody, with residents in Italy matching L1-Italian sentence stress patterns closely, prosodic attrition was only reported for residents in Italy in exploratory analyses. Overall, this study supports the notion of L1 attrition as a natural consequence of bilingualism—one that is domain- and experience-dependent, unfolds along a continuum, and involves a complex (and possibly inverse) relationship between L1 and L2 performance that warrants further investigation. Full article

Customers are the cornerstone of business success across industries. Companies invest significant resources in acquiring new customers and, more importantly, retaining existing ones. However, customer churn remains a major challenge, leading to substantial financial losses. Addressing this issue requires a deep understanding of customers’ cognitive status and behaviours, as well as early signs of churn. Predictive and Machine Learning (ML)-based analysis, when trained with appropriate features indicative of customer behaviour and cognitive status, can be highly effective in mitigating churn. A robust ML-driven churn analysis depends on a well-developed feature engineering process. Traditional churn analysis studies have primarily relied on demographic, product usage, and revenue-based features, overlooking the valuable insights embedded in customer–company interactions. Recognizing the importance of domain knowledge and human expertise in feature engineering and building on our previous work, we propose the Customer Churn-related Knowledge Base (ChurnKB) to enhance feature engineering for churn prediction. ChurnKB utilizes textual data mining techniques such as Term Frequency-Inverse Document Frequency (TF-IDF), cosine similarity, regular expressions, word tokenization, and stemming to identify churn-related features within customer-generated content, including emails. To further enrich the structure of ChurnKB, we integrate Generative AI, specifically large language models, which offer flexibility in handling unstructured text and uncovering latent features, to identify and refine features related to customer cognitive status, emotions, and behaviours. Additionally, feedback loops are incorporated to validate and enhance the effectiveness of ChurnKB.Integrating knowledge-based features into machine learning models (e.g., Random Forest, Logistic Regression, Multilayer Perceptron, and XGBoost) improves predictive performance of ML models compared to the baseline, with XGBoost’s F1 score increasing from 0.5752 to 0.7891. Beyond churn prediction, this approach potentially supports applications like personalized marketing, cyberbullying detection, hate speech identification, and mental health monitoring, demonstrating its broader impact on business intelligence and online safety. Full article

This paper analyzes spatial gestures and cognition in a new, or so-called “emerging”, visual language, the Yucatec Maya Sign Language (YSML). This sign language was created by deaf and hearing signers in various Yucatec Maya villages on the Yucatec Peninsula (Mexico). Although the sign language is not a signed version of spoken Yucatec Maya, both languages evolve in a similar cultural setting. Studies have shown that cultures around the world seem to rely on one preferred spatial Frame of Reference (FoR), shaping in many ways how people orient themselves and think about the world around them. Prior research indicated that Yucatec Maya speakers rely on the use of the geocentric FoR. However, contrary to other cultures, it is mainly observable through the production of gestures and not speech only. In the case of space, gestures in spoken Yucatec Maya exhibit linguistic features, having the status of a lexicon. Our research question is the following: if the preferred spatial FoR among the Yucatec Mayas is based on co-expressivity and spatial linguistic content visually transmitted via multimodal interactions, will deaf signers of an emerging language created in the same cultural setting share the same cognitive preference? In order to answer this question, we conducted three experimental tasks in three different villages where YMSL is in use: a non-verbal rotation task, a Director-Matcher task and a localization task. Results indicate that YMSL signers share the same preference for the geocentric FoR. Full article

In this paper, I explore metalinguistic discourse in Zinacantec Family Homesign (‘Z sign’), an emergent sign language developed by three deaf siblings and their hearing family members. In particular, I examine how metalinguistic discourse unfolds between a hearing Z signer and various members of her family—including her deaf siblings, her elderly hearing father, and her young hearing son. I do so via a close examination of several snippets of conversation in which the Z signers talk about the “right” way to sign, paying close attention to how they mobilize various semiotic devices, including manual signs, eye gaze, facial expressions, and speech. I aim to understand not only the formal components of metalinguistic discourse in Z sign but also how it functions as a form of social action in this small linguistic community. How do members of this family position themselves and others as (in)competent, (non-)authoritative signers in light of existing social divisions among them? How do they reinforce or challenge those social divisions through metalinguistic discourse? How might metalinguistic discourse contribute to the propagation of emergent linguistic norms throughout the family? I find that a recurrent device for enacting metalinguistic critique among the Z signers is the partial re-production and transformation of others’ utterances and other visible actions, manifested in a way that exploits the availability of multiple, semi-independent manual and non-manual articulators in the visual modality. Full article

Sign language serves as the primary mode of communication for the deaf community. With technological advancements, it is crucial to develop systems capable of enhancing communication between deaf and hearing individuals. This paper reviews recent state-of-the-art methods in sign language recognition, translation, and production. Additionally, we introduce a rule-based system, called ruLSE, for generating synthetic datasets in Spanish Sign Language. To check the usefulness of these datasets, we conduct experiments with two state-of-the-art models based on Transformers, MarianMT and Transformer-STMC. In general, we observe that the former achieves better results (+3.7 points in the BLEU-4 metric) although the latter is up to four times faster. Furthermore, the use of pre-trained word embeddings in Spanish enhances results. The rule-based system demonstrates superior performance and efficiency compared to Transformer models in Sign Language Production tasks. Lastly, we contribute to the state of the art by releasing the generated synthetic dataset in Spanish named synLSE. Full article

This study focused on assessing the language needs of English-speaking animal professionals in their interactions with Hispanic/Spanish-speaking animal caretakers. A survey was administered to a target audience of non-Spanish speaking and bilingual animal professionals to identify communication gaps while interacting with Hispanic/Spanish-speaking animal caretakers. The data was analyzed with descriptive and inferential statistics, including ordinal regression analyses to examine the impact of demographic variables on respondents’ answer choices. The results showed that English-speaking professionals struggled with written and oral communication, which differed compared to bilingual professionals (p < 0.05). Additionally, responses of female professionals varied regarding the aspects of Spanish necessary for interacting with Hispanic/Spanish-speaking animal caretakers, as well as the topics likely to be addressed when agriculture professionals communicate with animal caretakers (p < 0.05). Communication difficulties in the oral medium for both oral receptive skills (listening) and oral productive skills (speaking) were reported as the major barriers that animal professionals need to overcome in their attempt to communicate with the Hispanic/Spanish-speaking workforce in farm settings. This emphasizes the need to address oral communication barriers, and to a lesser degree, the development of reading and writing skills. The topics: typical clinical signs of illness, euthanasia, treatment—drugs, and identification of sick or injured animals were identified as the most likely to be addressed during on-farm interactions. These findings indicate that there are gaps in communication that need to be overcome to improve communication with on-farm Hispanic/Spanish-speaking animal caretakers and consequently contribute to enhancing animal health, welfare, and production. Full article

Linguistic landscape (LL) studies in bilingual regions can reveal power dynamics between two languages, providing important information regarding their status and vitality. To analyze the relationship between Spanish and English in Ciudad Juárez, a city on the south side of the U.S.-Mexico border, we collected 1649 pictures of public signs in several sections of the city, whose “wellness levels” differ from each other. Pictures were coded for several factors, including language choice, business type, sign type, and the main and informative section, amongst others. Results show that while Spanish is the most frequently used language, English has a strong presence in the LL of Ciudad Juárez. The main factor affecting language choice is “business type”. Certain businesses within the “beauty” category tend to favor the use of English, while businesses within the “home” category favor the use of Spanish. An analysis of socio-economic status (SES) and language choice revealed a direct relationship between them: English is favored in high-income neighborhoods, while Spanish is favored used in low-income areas. The analysis of the main and informative sections on signs further confirmed the prestige assigned to English, which appears mostly in the main and most prominent sections of a sign. Our research shows that although Spanish vitality in Ciudad Juárez is strong, English is used in advertising because it is prestigious and increases the value of products and services, making them more appealing to shoppers. Full article

Along with declaratives and interrogatives, imperatives are one of the three major clause types of human language. In Spanish, imperative verb forms present poor morphology, yet complex syntax. The present study examines the acquisition of (morpho)syntactic properties of imperatives in Spanish among English-speaking heritage speakers of Spanish. With the use of production and acceptability judgment tasks, this study investigates the acquisition of verb morphology and clitic placement in canonical and negative imperatives. The results indicate that the acquisition of Spanish imperatives among heritage speakers is shaped by the heritage speakers’ productive vocabulary knowledge, lexical frequency and syntactic complexity. Indeed, most of the variability in their knowledge was found in their production of negative imperatives: heritage speakers show a rather stable receptive grammatical knowledge while their production shows signs of variability modulated by the heritage speakers’ productive vocabulary knowledge and by the lexical frequency of the verb featured in the test items. Full article

Several researchers have proposed systems with high recognition rates for sign language recognition. Recently, there has also been an increase in research that uses multiple recognition methods and further fuses their results to improve recognition rates. The most recent of these studies, skeleton aware multi-modal SLR (SAM-SLR), achieved a recognition rate of 98.00% on the RGB video of the Turkish Sign Language dataset AUTSL. We investigated the unrecognized parts of this dataset and found that some signs where the fingers touch parts of the face were not correctly recognized. The proposed method is as follows: First, those with slight differences in top-1 and top-2 evaluation values in the SAM-SLR recognition results are extracted and re-evaluated. Then, we created heatmaps of the coordinates of the index finger in one-handed sign language in the face region of the recognition result in the top-1 to top-3 training data of the candidates based on the face part criteria, respectively. In addition, we extracted four index finger positions from the test data where the index finger stayed longer and obtained the product of the heatmap values of these positions. The highest value among them was used as the result of the re-evaluation. Finally, three evaluation methods were used: the absolute and relative evaluation with two heatmaps and an evaluation method integrating the absolute and relative evaluation results. As a result of applying the proposed method to the SAM-SLR and the previously proposed model, respectively, the best method achieved 98.24% for the highest recognition rate, an improvement of 0.30 points. Full article

As a typical sequence to sequence task, sign language production (SLP) aims to automatically translate spoken language sentences into the corresponding sign language sequences. The existing SLP methods can be classified into two categories: autoregressive and non-autoregressive SLP. The autoregressive methods suffer from high latency and error accumulation caused by the long-term dependence between current output and the previous poses. And non-autoregressive methods suffer from repetition and omission during the parallel decoding process. To remedy these issues in SLP, we propose a novel method named Pyramid Semi-Autoregressive Transformer with Rich Semantics (PSAT-RS) in this paper. In PSAT-RS, we first introduce a pyramid Semi-Autoregressive mechanism with dividing target sequence into groups in a coarse-to-fine manner, which globally keeps the autoregressive property while locally generating target frames. Meanwhile, the relaxed masked attention mechanism is adopted to make the decoder not only capture the pose sequences in the previous groups, but also pay attention to the current group. Finally, considering the importance of spatial-temporal information, we also design a Rich Semantics embedding (RS) module to encode the sequential information both on time dimension and spatial displacement into the same high-dimensional space. This significantly improves the coordination of joints motion, making the generated sign language videos more natural. Results of our experiments conducted on RWTH-PHOENIX-Weather-2014T and CSL datasets show that the proposed PSAT-RS is competitive to the state-of-the-art autoregressive and non-autoregressive SLP models, achieving a better trade-off between speed and accuracy. Full article

Fingerspelling is a critical component of many sign languages. This manual representation of orthographic code is one key way in which signers engage in translanguaging, drawing from all of their linguistic and semiotic resources to support communication. Translanguaging in bimodal bilinguals is unique because it involves drawing from languages in different modalities, namely a signed language like American Sign Language and a spoken language like English (or its written form). Fingerspelling can be seen as a unique product of the unified linguistic system that translanguaging theories purport, as it blends features of both sign and print. The goals of this paper are twofold: to integrate existing research on fingerspelling in order to characterize it as a cognitive-linguistic phenomenon and to discuss the role of fingerspelling in translanguaging and communication. We will first review and synthesize research from linguistics and cognitive neuroscience to summarize our current understanding of fingerspelling, its production, comprehension, and acquisition. We will then discuss how fingerspelling relates to translanguaging theories and how it can be incorporated into translanguaging practices to support literacy and other communication goals. Full article

Introduction: In a few cases, neurodegenerative diseases debut with a speech disorder whose differential diagnosis can be difficult. Case Report: We describe the case of a right-handed woman with a progressive speech impairment, which debuted when she was 80 years old. We report the results of neurological, neuropsychological, and imaging assessments with positron emission tomography (PET) over a period of nine years. Metabolic PET with 18F-FDG was performed at the age of 81 and repeated two years later due to the worsening of symptoms; amyloid PET with 18F-flutemetamol was performed at the age of 86. All PET results were quantitatively analyzed. A speech impairment remained the isolated neurological symptom for a long time, together with a mood disorder. Early FDG-PET showed hypometabolism in the left superior and inferior frontal areas, in the left superior temporal area, and in the right superior frontal area. Two years later, the hypometabolic area was more extensive. Amyloid PET was qualitatively and quantitatively normal. Nine years after the first symptoms, the speech production progressively worsened until complete anarthria, in association with writing impairment onset and signs of behavioral impairments. No signs of motor involvement were found. Conclusions: A progressive articulatory disorder without an evolution of motor disorders may be a distinct neurological degenerative entity, mainly affecting speech production for very a long time and with a specific early metabolic pattern in brain FDG-PET in the language production area. Monitoring patients with FDG-PET could predict the disease evolution years before a clinical deterioration. Full article