Role Of Speaker Research Articles

From the kitchen to pop culture: The role of Mansi heritage speakers in language shift and language revitalisation

Abstract Mansi is a severely endangered minority language spoken mainly by the Mansi, an indigenous people of the Russian North. Traditionally the Mansi were living on fishing, hunting, gathering, and reindeer breeding, but as a result of industrialisation in the region, they gradually moved to urban types of settlements. Since the beginning of the 21st century the heritage language speakers became visible as a distinctive category beside the group of Mansi native speakers. The Mansi heritage language speakers have less proficiency in Mansi, but they are more active and creative in negotiating the position of their language and culture. As a result of the heritage language speakers’ activity, Mansi is not only the language of the kitchen small talks, but also became the language of the contemporary indigenous pop culture.

Explaining the Dynamics and Stability of Dialects: A Representational Approach

Abstract In this article, the focus is on the pivotal role of speakers in shaping language dynamics and dialectal stability, particularly within the context of dialectal variation. It is evident that language is intricately tied to human experience, serving as a tool for navigation, problem-solving, and social interaction. This article posits that understanding the interplay between language dynamics and stability of dialects requires a nuanced consideration of speakers and their practical relationships with the world as well as their linguistic mental representations. People are not passive recipients of language; rather, they actively engage with it in various contexts, adapting to new situations and influencing linguistic change. Through empirical examples from German dialectology, the article illustrates how speakers’ interactions with their environment shape language evolution. Overall, the article aims to provide insight into the role of speakers in driving linguistic change and maintaining linguistic conventions within dialectal contexts. By examining the practical relationships between speakers and their environment, it contributes to the development of a comprehensive framework for understanding the complexities of language variation and evolution considering linguistic representations.

Breaking the Glass Ceiling: the Evolution of Female Speaker Representation and Visibility At American Orthopaedic Foot & Ankle Society Meetings Over Time

Category: Other Introduction/Purpose: Although female students comprise over half of U.S. undergraduate and medical school enrollment, representation among residents and practicing surgeons in orthopaedics remains disproportionately low at 15% and 6%, respectively. The decline in residency may stem from a lack of early exposure to female mentors. This study investigates female representation in speaker roles at American Orthopaedic Foot & Ankle Society (AOFAS) meetings over time. Methods: The annual AOFAS meeting programs for 2012, 2017, and 2022 were reviewed by three independent raters. Each speaker, moderator, and panelist was classified based on sex and role; 15% of the data was cross-checked and evaluated using Fleiss Multirater Kappa validation. Sessions discussing surgical or biomedical topics were categorized as “technical”, and all other sessions (i.e., welcome sessions) were categorized as “nontechnical.” Individual-year odds ratios (ORs) and confidence intervals (CIs) evaluating sex versus session status, as well as sex versus speaker role, are provided. Combined results controlling for year were calculated using the Cochran-Mantel-Haenszel method. Results: A total of 403 speaking sessions were analyzed; 12% of sessions were led by female speakers. On average, female speakers were significantly more likely than males to assume nontechnical speaking roles across the three years combined (OR 3.84; 95% CI, 1.43 to 10.33). Female speakers led 12.7% of the 381 technical sessions. Females also comprised 9.8% and 16.7% of moderator and panelist roles, respectively. Conclusion: Although our study reveals an increasing trend in female speakers, panelists, and moderators from 2012 to 2022, these data demonstrate a persistent lack of sex diversity at AOFAS annual meetings, especially within technical sessions and moderator roles. Increasing female representation at conferences while fostering mentorship opportunities for medical students may serve as a valuable opportunity to address disparities between males and females within orthopaedics. Female Representation in Speaker Roles at AOFAS and Session Category Odds Ratios

Why Conceptual Engineers Should Resist Dialogical Individualism

Conceptual engineering has strong political roots. But if conceptual engineering is to be a useful tool for promoting social justice, there must be a means by which the concepts we design can take root and propagate in dominant contexts. This is known as the implementation challenge. In this paper, I caution against movements toward a particular methodological perspective on the challenge called dialogical individualism. This perspective centres the role of speakers in speech-situations to persuade hearers to change their minds about currently held concepts. This individualism has a distorting effect: it warps our perception of the size of the challenge. In particular, dialogical individualism ignores the social environmental factors that make conversation an unfriendly site for conceptual change. Moreover, it is not sufficiently attentive to the history of conceptual change in communities of practice. In the end, I argue for a methodological perspective shift: discursive strategies, such as speaker persuasion, should be decentralized in our overall thinking about the best solutions to the implementation challenge. Our attention is better focused on tailoring strategies to deal with the social environment in which concept-users are embedded.

The use of guest speakers in higher education and implications for pharmaceutical teaching: a systematic review of literature

Background The purpose of this paper was to systematically review the current literature on the use of guest speakers in higher education teaching and evaluate the implications of the findings for teaching in pharmaceutical teaching. Methods A comprehensive search of different academic databases for literature on the use of guest speakers in higher education teaching was conducted and articles meeting the inclusion criteria were included in the analysis. A total of 15 articles were used in this systematic review. Results The use of guest speakers has critical benefits including promoting better learning, good career preparedness, positive learning outcomes, and creating an environment where learners have the opportunity to perceive real-world scenarios from the experiences of the guest speakers and thus be better prepared for the job market. With the increasing importance of the role of guest speakers in higher education learning, researchers have been engaging in coming up with standards and best practices for enhancing the effectiveness of the use of guest speakers in learning. The use of guest speakers in the teaching of pharmacy can enhance positive health outcomes by allowing students to have a better view of the situations they will deal with in their careers. Conclusion The use of guest speakers can have major positive outcomes in promoting effectiveness in learning among students of pharmacy. Professors teaching pharmacy courses have the opportunity to benefit from various tools and resources that academic researchers have developed for guiding the process of the use of guest speakers in pharmacy teaching.

Becoming a language teacher educator: An outsider perspective

This is a reflective piece theorizing my personal and academic experiences working with preservice teachers who are pursuing a Teaching English as a Second Language Certificate with immersion experience participating in a study abroad program teaching English to university students in Ecuador. Teaching predominantly white students as a woman of color is always full of stories, both real and imaginary. This is an opportunity to theorize the role of non-native English speakers guiding preservice teachers to teach English learners in the global south while discussing or contesting language aspects such as pronunciation, accuracy, proficiency, among others.

Learner corpus research: a critical appraisal and roadmap for contributing (more) to SLA research agendas

Abstract Over the past decade, learner corpora have gained recognition as valuable data sources in Second Language Acquisition (SLA) research. This development can be attributed to significant progress in Learner Corpus Research (LCR). However, there is still substantial work to be done. This article highlights key issues essential for sustaining the relevance of learner corpora in SLA. More particularly, I focus on the need for more diverse types of learner corpora, stress the importance of detailed metadata, and advocate for multifactorial study designs. I then revisit ongoing debates regarding the role of the native speaker in LCR and propose a practical solution to address this thorny issue. Finally, I also readdress the need for improvement in the quantitative methods and statistics, arguing that the importance of robust quantitative analysis cannot be overstated. In conclusion, I envision an ambitious learner corpus compilation project that adheres to the FAIR principles, with the goal of further elevating study quality in LCR.

On the role of speaker’s intentions in shaping ‘what is said’ when uttering a sentence

On the role of speaker’s intentions in shaping ‘what is said’ when uttering a sentence

Who do learners of English as a lingua franca want to sound like? English speaker role models and envisioned selves in imagined communities

AbstractTo examine speaker role models (SRMs) in second language acquisition (SLA), this study explored the sociolinguistic English as a lingua franca (ELF) perspective targeting international intelligibility. Thus, it examined the way ELF learners align with self‐selected English speakers and anonymous (audio‐recorded) English speakers as potential SRMs. The researchers asked the participants, 57 Iranian English majors, “Who do you want to sound like in English and why?” and analyzed their answers in the context of their SRMs and envisioned selves in imagined communities (ICs). The study's findings revealed that most participants had SRMs with three sets of characteristics—high English language proficiency and intelligibility, likeable personal attributes, and notable professional accomplishments. To explore anonymous English speakers in particular as potential SRMs, the researchers asked participants to rate anonymous speakers' intelligibility and likeability. The findings established that, based on the sound of their voices alone, anonymous audiorecorded speakers were less likely to be selected as SRMs. Further, the study found no significant difference between anonymous native and nonnative speakers, celebrities and others, for whom accent intelligibility and likeability increased but did not determine the likelihood of selecting them as their SRMs. Based on its findings, this study draws implications for language and teacher education and offers classroom applications with specific activities.

Positioning of applicants in asylum interviews: Case officers as recontextualising agents

Abstract This study aims to develop an understanding of how different communicative strategies used by case officers in asylum interviews may position applicants in various ways. The analysis focuses on a relatively standardised sequence at the start of asylum interviews, where the communicative situation and its legal framework are explained to the applicant. Case officers use guidelines to support them with this process. Using a comparative discourse analysis of excerpts from two asylum interviews, I examine the discursive means by which the applicants are positioned in the case officers’ utterances, drawing mainly on the concepts of positioning and recontextualisation. The findings show how case officers’ instructive statements could be used as a resource not only to provide information to the applicants but also to position asylum seekers in a respectful way. (Asylum interview, intertextuality, positioning, recontextualisation, speaker role)*

Neural Network-Based Approach to Detect and Filter Misleading Audio Segments in Classroom Automatic Transcription

Audio recording in classrooms is a common practice in educational research, with applications ranging from detecting classroom activities to analyzing student behavior. Previous research has employed neural networks for classroom activity detection and speaker role identification. However, these recordings are often affected by background noise that can hinder further analysis, and the literature has only sought to identify noise with general filters and not specifically designed for classrooms. Although the use of high-end microphones and environmental monitoring can mitigate this problem, these solutions can be costly and potentially disruptive to the natural classroom environment. In this context, we propose the development of a novel neural network model that specifically detects and filters out problematic audio sections in classroom recordings. This model is particularly effective in reducing transcription errors, achieving up to a 96% success rate in filtering out segments that could lead to incorrect automated transcriptions. The novelty of our work lies in its targeted approach for low-budget, aurally complex environments like classrooms, where multiple speakers are present. By allowing the use of lower-quality recordings without compromising analysis capability, our model facilitates data collection in natural educational settings and reduces the dependency on expensive recording equipment. This advancement not only demonstrates the practical application of specialized neural network filters in challenging acoustic environments but also opens new avenues for enhancing audio analysis in educational research and beyond.

La problemática y el tratamiento de la competencia sociolingüística y la competencia pragmática en la clase de ELE desde un enfoque novedoso

The purpose of our article is to analyze the main differences between sociolinguistic competence and pragmatic competence, integrated within communicative competence. Firstly, we will try to define, characterize, and exemplify the tools inherent to sociolinguistic competence in comparison with pragmatic competence. We will present that courtesy formulas in language teaching should be included within the pragmatic competence and not sociolinguistic as it has been done usually. To do this, we will use the multilingual competence on which the CEFR-CV (2020) places considerable emphasis. Likewise, the concepts of sociolinguistic and pragmatic competences will be explained taking as a starting point the components of communicative competence which, in turn, encompasses intercultural competences. On the other hand, we will also deal with the role and challenges of the intercultural speaker as a mediator of pragmatic, sociolinguistic and sociocultural meanings. In the last part of the article, we will focus on the field of teaching Spanish as a foreign language (hereinafter ELE), specifically, on the development of communicative competence from a sociolinguistic and pragmatic perspective. We will analyze some ELE manuals to reflect on and show the work proposals related to pragmatic and sociolinguistic knowledge (especially at level A1) carried out by their authors.

A Keynote Address: A Guide to Supporting Conference Speakers with Lived Experience of Cleft Lip and/or Palate.

Although the value of diversity within academia and society is increasingly recognised, the role of speakers with lived experience at cleft and craniofacial conferences remains inconsistent. This perspectives article shares reflection from three academics with lived experience of cleft discussing the value of including lived experience speakers routinely within conferences and outlining common challenges and barriers to the involvement of "experts-by-experience". Key considerations and recommendations are offered to help conference organisers and delegates to make the most of the lived experience perspective, while ensuring the conference experience is positive for lived experience speakers.

Smart Speaker and ICT Use in Relationship With Social Connectedness During the Pandemic: Loneliness and Social Isolation Found in Older Adults in Low-Income Housing.

Social well-being of older adults living in low-income housing was disproportionately affected by the coronavirus disease 2019 pandemic. We explored low-income residents' experiences of social isolation and loneliness and strategies to remain socially connected during the pandemic. As part of a larger, 3-phase user-centered design study, we conducted a qualitative study using focus groups to gain insights into social isolation experiences and the role of information and communication technologies (ICTs), including smart speakers, in social connectedness (N = 25, 76% African American). We also collected survey data to describe social isolation, loneliness, and current ICT use in the sample. Participants included both smart speaker users and nonusers. Experiences of social isolation and loneliness varied by participants' sociodemographic characteristics and previous experiences with smart speakers. Qualitative analysis showed participants demonstrated coping strategies developed during the pandemic to adapt to new norms of connecting with others, including technology-enabled social interactions. Participants expressed a strong desire to build community together in their facilities and highlighted the potential role of smart speakers in making meaningful social connections, encompassing safety checks to have a means for emergencies, and providing a virtual companion. Access, digital literacy, training, security, and privacy issues were discussed as factors affecting their adoption of new ICT for enhanced social connectedness. This study highlights the importance of understanding the unique social isolation experience, demographics, and social determinants of health of low-income residents to develop ICT-based interventions for social connectedness.

An Automatic Speaker Clustering Pipeline for the Air Traffic Communication Domain

In air traffic management (ATM), voice communications are critical for ensuring the safe and efficient operation of aircraft. The pertinent voice communications—air traffic controller (ATCo) and pilot—are usually transmitted in a single channel, which poses a challenge when developing automatic systems for air traffic management. Speaker clustering is one of the challenges when applying speech processing algorithms to identify and group the same speaker among different speakers. We propose a pipeline that deploys (i) speech activity detection (SAD) to identify speech segments, (ii) an automatic speech recognition system to generate the text for audio segments, (iii) text-based speaker role classification to detect the role of the speaker—ATCo or pilot in our case—and (iv) unsupervised speaker clustering to create a cluster of each individual pilot speaker from the obtained speech utterances. The speech segments obtained by SAD are input into an automatic speech recognition (ASR) engine to generate the automatic English transcripts. The speaker role classification system takes the transcript as input and uses it to determine whether the speech was from the ATCo or the pilot. As the main goal of this project is to group the speakers in pilot communication, only pilot data acquired from the classification system is employed. We present a method for separating the speech parts of pilots into different clusters based on the speaker’s voice using agglomerative hierarchical clustering (AHC). The performance of the speaker role classification and speaker clustering is evaluated on two publicly available datasets: the ATCO2 corpus and the Linguistic Data Consortium Air Traffic Control Corpus (LDC-ATCC). Since the pilots’ real identities are unknown, the ground truth is generated based on logical hypotheses regarding the creation of each dataset, timing information, and the information extracted from associated callsigns. In the case of speaker clustering, the proposed algorithm achieves an accuracy of 70% on the LDC-ATCC dataset and 50% on the more noisy ATCO2 dataset.

Boosting Low-Resource Speech Recognition in Air Traffic Communication via Pretrained Feature Aggregation and Multi-Task Learning

Developing a robust Automatic Speech Recognition (ASR) system usually requires a large amount of well-annotated samples which is extremely hard to build in the Air Traffic Control (ATC) due to domain-specific knowledge. In this work, we present a novel approach to improve ASR performance in the ATC domain by integrating Self-Supervised Learning and Multi-Task learning into a unified framework. Specifically, the proposed framework follows a two-stage training paradigm, i.e., (a) learning universal acoustic representations by employing the wav2vec 2.0 model and (b) jointly finetuning the model by the ASR, Speaker Role Identification, and Language Identification tasks. To capture the task-specific representations, an attention-guided feature aggregation module is dedicatedly designed to disentangle the discriminative representations from the pretrained features. In addition, the uncertainty-based loss combination strategy is employed to balance the loss weights for each task in a learnable manner. Finally, we conduct experiments to validate the technical improvements in a real-world ATC dataset. Experimental results demonstrated that the proposed framework outperforms competitive baselines among all tasks.

The influence of task complexity and task modality on learners’ topic and turn management

Abstract Peer interaction is examined as an important indicator of performance in task-based language learning. However, little research has explored learners’ interactional competence under the influences of task factors. This study investigates the effects of task complexity and task modality on learners’ interactional competence in terms of topic management and turn management. Four tasks were designed – written-simple, written-complex, oral-simple, and oral-complex – and 40 Chinese EFL learners completed them in counterbalanced sequences. The results showed the significant influences of task complexity and task modality on learners’ topic and turn management. Task modality and complexity interactively influenced learners when they were expanding on topics in the role of the current speaker. Considering the cognitive demands of increasing complexity and differences between the two modalities, this paper discusses the implications of the findings for developing L2 interactional competence in speech- and text-based interactions.

An Adaptive Layer to Leverage Both Domain and Task Specific Information from Scarce Data

Many companies make use of customer service chats to help the customer and try to solve their problem. However, customer service data is confidential and as such, cannot easily be shared in the research community. This also implies that these data are rarely labeled, making it difficult to take advantage of it with machine learning methods. In this paper we present the first work on a customer’s problem status prediction and identification of problematic conversations. Given very small subsets of labeled textual conversations and unlabeled ones, we propose a semi-supervised framework dedicated to customer service data leveraging speaker role information to adapt the model to the domain and the task using a two-step process. Our framework, Task-Adaptive Fine-tuning, goes from predicting customer satisfaction to identifying the status of the customer’s problem, with the latter being the main objective of the multi-task setting. It outperforms recent inductive semi-supervised approaches on this novel task while only considering a relatively low number of parameters to train on during the final target task. We believe it can not only serve models dedicated to customer service but also to any other application making use of confidential conversational data where labeled sets are rare. Source code is available at https://github.com/gguibon/taft

Gender disparity in prestigious speaking roles: A study of 10 years of international conference programming in the field of gambling studies.

The objective of this study was to examine the distribution of prestigious speaking roles by gender at gambling studies conferences to better understand the state of gender representation within the field. Keyword searches were conducted in the fall of 2019. A total of 16 conferences that occurred between 2010-2019 and comprising 882 prestigious speaking opportunities were included. Quantitative analysis (i.e., t-tests, chi-squared posthoc tests) was undertaken to evaluate the representation of women speakers and if proportions were the same across genders for speakers. There were significantly less women than men within prestigious speaking roles at gambling studies conferences with only 30.2% of speakers being women (p < .001). This underrepresentation of women was consistent across conference location, speaker continent, speaker role, time, and across the majority of conferences. Women held prestigious speaking roles less frequently than men (M = 1.48 vs. 1.76; p < .001). A 9 to 1 (p < .001) ratio of men to women was found among top 10 most frequent prestigious speakers. While there was a higher proportion of women than men among student speakers and there was no significant gender disparity among early career researchers, there was a significantly lower proportion of women than men among speakers who hold more senior academic positions. There is an issue of gender disparity in prestigious speaking roles at conferences within the gambling studies field. This study highlights the need to counteract gender disparities and make room for diversity within the field.

Is Hearing Really Believing?

Abstract: Smart speakers are becoming popular all over the world and offer an alternative to conventional web search. We conducted two experiments to investigate whether different message modalities affect credibility perceptions, which role sponsor credibility and message accuracy play, and if this role differs in the two modalities. Based on the MAIN Model by Sundar (2008) , we assumed that modality, that is, whether the information is given textually or aurally, can affect credibility assessments. To investigate this, two online experiments with a 2 (modality: smart speaker/search engine) × 2 (message accuracy: high/low) ×3 (sponsor credibility: high/low/none) mixed factorial design were conducted ( n = 399 and 398). Information presented by the voice of a smart speaker was generally perceived as more credible. Results further showed that no source attribution and low message accuracy affected message credibility less in the auditive than in the textual modality, especially for participants with less topic involvement. With this, we gained valuable insights into the role of smart speakers for information search and potential downsides of this usage.