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Whilst, in many countries, the sudden enforced transfer to large-scale distance learning in state schools as a result of COVID_19 lockdown measures caused turmoil, it also provided an unprecedented opportunity to understand more about key factors associate ...
Subword modeling for zero-resource languages aims to learn low-level representations of speech audio without using transcriptions or other resources from the target language (such as text corpora or pronunciation dictionaries). A good representation should ...
The need for good software training is essential in the HEP community. Unfortunately, current training is non -homogeneous and the definition of a common baseline is unclear, making it difficult for newcomers to proficiently join large collaborations such ...
Through their role in labs, exercise/recitation sessions and tutorials, graduate or doctoral teaching assistants play a significant role in the education of engineering students. Yet doctoral assistants frequently get little pedagogical training, what trai ...
In this paper, we introduce a novel approach for Language Identification (LID). Two commonly used state-of-the-art methods based on UBM/GMM I-vector technique, combined with a back-end classifier, are first evaluated. The differential factor between these ...
Course design in higher education is often approached in a very linear and text-based manner. The paper presents a visual tool in the form of a canvas aimed at accompanying teachers in the design of courses. The canvas can be used in an individual or co-te ...
The multi-level adaptive networks (MLAN) technique is a cross-lingual adaptation framework where a bottleneck (BN) layer in a deep neural network (DNN) trained in a source lan- guage is used for producing BN features to be exploited in a second DNN in a ta ...
The quality of teaching is significantly enhanced through feedback to teachers about their teaching. Whereas systems to show student learning exist, those showing the emotional state of the classroom do not. We argue that such systems could greatly improve ...
"Teaching analytics" is the application of learning analytics techniques to understand teaching and learning processes, and eventually enable supportive interventions. However, in the case of (often, half-improvised) teaching in face-to-face classrooms, su ...
One of the key challenges involved in building statistical automatic speech recognition (ASR) systems is modeling the relationship between subword units or “lexical units” and acoustic feature observations. To model this relationship two types of resources ...