The benefits and pitfalls of language change – The case of gender-fair language use

Gender-fair language (GFL) is a symmetric linguistic treatment of women and men. To create GFL two principle strategies can be deployed. Neutralization means that gender-unmarked forms (police officer) are used to substitute the male-biased (policeman). Feminization, implies that feminine forms of nouns are used systematically to make female referents visible. The results of a comprehensive European research program provide evidence in support of a non-discrimination policy in language, yet identify the potential setbacks preventing linguistic reforms to be effective. In general, studies indicate positive effects of GFL. In an applied context, for example women feel more motivated to apply for the position if a job advertisement is formulated in a GFL. However, negative effects of reformed usage were also reported specifically when GFL is novel. For example, a woman referred to as a chairperson was evaluated lower in occupational status than a woman referred to as a chairman.

How gender fair are German schoolbooks in the twenty-first century? An analysis of language and illustrations in schoolbooks for mathematics and German

Schoolbooks convey not only school-relevant knowledge; they also influence the development of stereotypes about different social groups. Particularly during the 1970s and 1980s, many studies analysed schoolbooks and criticised the overall predominance of male persons and of traditional role allocations. Since that time, women’s and men’s occupations and social functions have changed considerably. The present research investigated gender portrayals in schoolbooks for German and mathematics that were recently published in Germany. We examined the proportions of female and male persons in pictures and texts and categorized their activities, occupational and parental roles. Going beyond previous studies, we added two criteria: the use of gender-fair language and the spatial arrangements of persons in pictures. Our results show that schoolbooks for German contained almost balanced depictions of girls and boys, whereas women were less frequently shown than men. In mathematics books, males outnumbered females in general. Across both types of books, female and male persons were engaged in many different activities, not only gendertyped ones; however, male persons were more often described via their profession than females. Use of gender-fair language has found its way into schoolbooks but is not used consistently. Books for German were more gender fair in terms of linguistic forms than books for mathematics. For spatial arrangements, we found no indication for gender biases. The results are discussed with a focus on how schoolbooks can be optimized to contribute to gender equality.

HPV knowledge, HPV vaccine awareness and initiation among Hispanics: The role of language, information seeking, and information scanning

Background. Among Hispanics, the HPV vaccine has the potential to eliminate disparities in cervical cancer incidence and mortality but only if optimal rates of vaccination are achieved. Media can be an important information source for increasing HPV knowledge and awareness of the vaccine. Very little is known about how media use among Hispanics affects their HPV knowledge and vaccine awareness. Even less is known about what differences exist in media use and information processing among English- and Spanish-speaking Hispanics.^ Aims. Examine the relationships between three health communication variables (media exposure, HPV-specific information scanning and seeking) and three HPV outcomes (knowledge, vaccine awareness and initiation) among English- and Spanish-speaking Hispanics.^ Methods. Cross-sectional data from a survey administered to Hispanic mothers in Dallas, Texas was used for univariate and multivariate logistic regression analyses. Sample used for analysis included 288 mothers of females aged 8-22 recruited from clinics and community events. Dependent variables of interest were HPV knowledge, HPV vaccine awareness and initiation. Independent variables were media exposure, HPV-specific information scanning and seeking. Language was tested as an effect modifier on the relationship between health communication variables and HPV outcomes.^ Results. English-speaking mothers reported more media exposure, HPV-specific information scanning and seeking than Spanish-speakers. Scanning for HPV information was associated with more HPV knowledge (OR = 4.26, 95% CI = 2.41 - 7.51), vaccine awareness (OR = 10.01, 95% CI = 5.43 - 18.47) and vaccine initiation (OR = 2.54, 95% CI = 1.09 - 5.91). Seeking HPV-specific information was associated with more knowledge (OR = 2.27, 95% CI = 1.23 - 4.16), awareness (OR = 6.60, 95% CI = 2.74 - 15.91) and initiation (OR = 4.93, 95% CI = 2.64 - 9.20). Language moderated the effect of information scanning and seeking on vaccine awareness.^ Discussion. Differences in information scanning and seeking behaviors among Hispanic subgroups have the potential to lead to disparities in vaccine awareness.^ Conclusion. Findings from this study underscore health communication differences among Hispanics and emphasize the need to target Spanish language media as well as English language media aimed at Hispanics to improve knowledge and awareness.^

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

Validation tool for smart screening of language disorders in pediatrics care

Primary-care pediatricians could play a key role in early detection of development disorders as quick as they might have enough time and knowledge for suitable screenings at clinical routine. This research paper focuses on the development and validation of a knowledge-based web tool whose aim is to support a smart detection of developmental disorders in early childhood. Thus, the use of the system can trigger the necessary preventive and therapeutic actions from birth until the age of six. The platform was designed on the basis of an analysis of significant 21 cases of children with language disorders that supported the creation of a specific knowledge base, its ontology and a set of description logic relations. The resulting system is being validated in a scalable approach with a team of seven experts from the fields of neonathology, pediatrics, neurology and language therapy.

Development of a Knowledge Base for smart screening of language disorders in primary care

Monitoring of neuro-evolutive development from birth until the age of six is a decisive factor in a child's quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in early detection of development alterations as they can undertake the preventive and therapeutic actions necessary in the interest of a child's optimal development. The focus of this research paper is the construction of a Knowledge Base for smart screening aimed to assist pediatricians in processes of early referral in language disorders. The proposed model provides health professionals with a decision-making tool that supports referral processes. In this way, essential diagnostic and/or therapeutic actions are triggered for a comprehensive individual development. The resulting system was developed on the basis of an analysis and verification of 21 cases of children with language disorders.

On the dynamic adaptation of language models based on dialogue information

We present an approach to adapt dynamically the language models (LMs) used by a speech recognizer that is part of a spoken dialogue system. We have developed a grammar generation strategy that automatically adapts the LMs using the semantic information that the user provides (represented as dialogue concepts), together with the information regarding the intentions of the speaker (inferred by the dialogue manager, and represented as dialogue goals). We carry out the adaptation as a linear interpolation between a background LM, and one or more of the LMs associated to the dialogue elements (concepts or goals) addressed by the user. The interpolation weights between those models are automatically estimated on each dialogue turn, using measures such as the posterior probabilities of concepts and goals, estimated as part of the inference procedure to determine the actions to be carried out. We propose two approaches to handle the LMs related to concepts and goals. Whereas in the first one we estimate a LM for each one of them, in the second one we apply several clustering strategies to group together those elements that share some common properties, and estimate a LM for each cluster. Our evaluation shows how the system can estimate a dynamic model adapted to each dialogue turn, which helps to improve the performance of the speech recognition (up to a 14.82% of relative improvement), which leads to an improvement in both the language understanding and the dialogue management tasks.

Deployment and validation of a smart system for screening of language disorders in primary care

Neuro-evolutive development from birth until the age of six years is a decisive factor in a child?s quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in its detection as they can undertake the preventive and therapeutic actions requested to promote a child?s optimal development. However, the lack of time and little specific knowledge at primary-care avoid to applying continuous early-detection anomalies procedures. This research paper focuses on the deployment and evaluation of a smart system that enhances the screening of language disorders in primary care. Pediatricians get support to proceed with early referral of language disorders. The proposed model provides them with a decision-support tool for referral actions to trigger essential diagnostic and/or therapeutic actions for a comprehensive individual development. The research was conducted by starting from a sample of 60 cases of children with language disorders. Validation was carried out through two complementary steps: first, by including a team of seven experts from the fields of neonatology, pediatrics, neurology and language therapy, and, second, through the evaluation of 21 more previously diagnosed cases. The results obtained show that therapist positively accepted the system proposal in 18 cases (86%) and suggested system redesign for single referral to a speech therapist in three remaining cases.