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Artificial neural networks (ANN) have become the mainstream acoustic modeling technique for large vocabulary automatic speech recognition (ASR). A conventional ANN features a multi-layer architecture that requires massive amounts of computation. The brain-inspired spiking neural networks (SNN) closely mimic the biological neural networks and can operate on low-power neuromorphic hardware with spike-based computation. Motivated by their unprecedented energy-efficiency and rapid information processing capability, we explore the use of SNNs for speech recognition. In this work, we use SNNs for acoustic modeling and evaluate their performance on several large vocabulary recognition scenarios. The experimental results demonstrate competitive ASR accuracies to their ANN counterparts, while require only 10 algorithmic time steps and as low as 0.68 times total synaptic operations to classify each audio frame. Integrating the algorithmic power of deep SNNs with energy-efficient neuromorphic hardware, therefore, offer an attractive solution for ASR applications running locally on mobile and embedded devices.

Language teachers are often masters of using the physical space in their language classrooms, rearranging furniture, groups, and artifacts to facilitate meaningful encounters with and among learners. Indeed, during the COVID‐19 crisis, many language teachers are sharing that these human encounters—reading learners' needs through body language, moving in and out of conversations, or engaging each other face‐to‐face—are the biggest felt loss in their emergent digital language classrooms. Yet, the new digital realities do not necessarily mean that teachers must sacrifice real collaboration among their learners. Digital tools were often designed to explicitly facilitate multimodal collaboration, and, with a wider variety of humans and human stories than may be found within the four walls of the typical classroom. This article aims to help language teachers facilitate more diverse interactions in the target language through the use of tools, spaces, and strategies that can be easily incorporated into our digital classrooms. We describe three categories of such activities (mobile‐assisted learning, tandem learning, and service‐learning) and explain how these can be most effectively incorporated into an online language class. The Challenge Videoconferencing tools such as Zoom are being widely used as an immediate response to remote language teaching needs. However, these tools are rarely ideal as a replacement for the classroom's physically embodied engagement. What alternatives exist for educators facilitating students' language growth and human collaboration?

This paper presents the findings of a six-week telecollaborative project between sixteen American students enrolled in a second-semester German class at an American university and sixteen German students enrolled in an advanced English course at a high school in Germany. Students discussed various cultural topics with their partner in two e-mails per week. The study strove to reveal the American college students' understanding of their own and of German culture, their interest in cultural learning, and possible changes therein through telecollaboration. Moreover, the study aimed at exploring if intercultural competence can be exhibited, and thus assessed, through an e-mail exchange. For that purpose, Byram's model of intercultural competence (1997) was used for the data analysis. In addition, pre- and post-surveys were administered to help answer one of the research questions. The results of the study revealed that students' interest in cultural learning did not change significantly. Additionally, the results showed that the majority of Byram's objectives can be demonstrated in an e-mail exchange.

Playing video games engages children and youth and offers a potential for learning in general and situated language learning in particular. The aim of this paper is to explore the situated conditions and affordances for facilitating in-game interaction, as well as to discuss the language learning potential and educational implications of these conditions. In this paper, this is discussed through two datasets: a) a pre-study, a survey among students in grades 4–7 (n = 65), as well as b) playtests with child volunteers (n = 6), conducted in pairs in a laboratory setting. The results are discussed in relation to interactional practices, what game genres and mechanics are relevant to tandem language learning and the implications that in-game competence might have on such learning.

This paper reports on crossing borders virtually via an e-Tandem scheme and presents the findings of a study, in which students of English from an Austrian university were paired with students of German from the UK and the USA. Drawing on data from 19 in-depth interviews, the study aims to identify links between e-Tandem language learning and foreign language enjoyment (FLE) (Dewaele & MacIntyre, 2014, 2016). A category-based qualitative text analysis (Kuckartz, 2014) revealed that a majority of the interviewees felt e-Tandem language learning contributed to their FLE. Furthermore, a range of reasons underlying students’ perceived enjoyment of learning a language in Tandem emerged: having authentic conversations in the target language with L1 (first language) users (Dewaele, 2018), perceiving each other as cultural mediators and a difference from language classroom contexts on the level of power relations, which made students feel more at ease. Helping each other, receiving one-on-one feedback and perceiving improvement in their linguistic mastery were furthermore mentioned as factors they felt boosted their enjoyment and so was developing friendships with L1 users. According to the interviewees, these aspects specifically increased their interest and enjoyment in using and learning the language and their eudaimonic happiness. The findings demonstrate that e-Tandem language learning can be a resource to enhance perceived enjoyment in foreign language learners at tertiary level and they illustrate that social and private components of FLE seem to be interlinked.

This article examines a study of seven learners who logged their experiences on the language leaning social networking site Livemocha over a period of three months. The features of the site are described and the likelihood of their future success is considered. The learners were introduced to the Social Networking Site (SNS) and asked to learn a language on the site. They were positive about two aspects of the site: the immediate peer-feedback available and the ability to converse synchronously and asynchronously with native speakers of their target language. However, there was universal criticism of the “word-list” based language learning materials and several participants complained about the regular cyber-flirting they encountered. Other aspects of the site including accessibility, ease of use, syllabus, activities, and relationships with other members are also considered. The potential for integrating some of the features of SNSs for language learning into the Higher Education (HE) curriculum and the implications of this for educators are also discussed.

Wound age estimation is one of the most challenging and indispensable issues for forensic pathologists. Although many methods based on physical findings and biochemical tests can be used to estimate wound age, an objective and reliable method for inferring the time interval after injury remains difficult. In the present study, endogenous metabolites of contused skeletal muscle were investigated to estimate the time interval after injury. Animal model of skeletal muscle injury was established using Sprague-Dawley rat, and the contused muscles were sampled at 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, and 48 h postcontusion (  = 9). Then, the samples were analysed using ultraperformance liquid chromatography coupled with high-resolution mass spectrometry. A total of 43 differential metabolites in contused muscle were determined by metabolomics method. They were applied to construct a two-level tandem prediction model for wound age estimation based on multilayer perceptron algorithm. As a result, all muscle samples were eventually divided into the following subgroups: 4, 8, 12, 16-20, 24-32, 36-40, and 44-48 h. The tandem model exhibited a robust performance and achieved a prediction accuracy of 92.6%, which was much higher than that of the single model. In summary, the multilayer perceptron-multilayer perceptron tandem machine-learning model based on metabolomics data can be used as a novel strategy for wound age estimation in future forensic casework. The changes of metabolite profile were correlated with the time interval after injury in contused skeletal muscle.A panel of 43 endogenous metabolites screened by ultraperformance liquid chromatography coupled with high-resolution mass spectrometry could distinguish the wound ages.The multilayer perceptron (MLP) algorithm exhibited a robust performance in wound age estimation using metabolites.The combination of matabolomics and MLP-MLP tandem model could improve the accuracy of inferring the time interval after injury.

The article attempts to approach stereotypes from both the theoretical and empirical perspectives. First, it endeavours to explain the term “stereotype”, looks into its characteristics and functions and then presents selected aspects of the Polish-German tandem project devoted to stereotypical thinking.

We present findings of a project that investigated the potential of an online tandem program to enhance the foreign language learning of two groups of school-aged beginner learners, one learning English in Colombia and the other learning Spanish in New Zealand. We assessed the impact of the project on students’ learning with a free writing activity done as pretest and posttest and used a semi-structured interview to explore their attitudes towards language learning and their perceived development of their native language. Data analysis indicated statistically significant gains in foreign language writing and positive attitudinal changes toward foreign and native language learning.

Tandem learning is the collaborative learning partnership of two language learners with complementary language combinations, for example an Irish student learning German and a German student learning English. One of the major principles in tandem learning, apart from reciprocity and learner autonomy, is balanced bilingualism. While learners may find it relatively easy to control their bilingualism in email exchanges, it is not so easy to do so in synchronous text-based exchanges in object-oriented multi-user domains (MOOs), where measurements of bilingualism are often crude and inaccurate. The purpose of this paper is twofold. First, we wanted to develop and test a computerized tool, the Bilingual Tandem Analyser, that automatically analyzes and provides feedback on the languages that are used during a \"live\" exchange. Second, we wanted to implement the tool in a bilingual exchange between German and Irish students to see whether the balance in bilingualism improved. Our results show that the Bilingual Tandem Analyser is quick, reliable, and highly accurate for the four languages tested. When implementing the tool, we noticed that there is a noticeable improvement towards more balanced exchanges but that more work is needed on the pedagogical implementation.