Vocabulary

A vocabulary (also known as a lexicon) is a set of words, typically the set in a language or the set known to an individual. The word vocabulary originated from the Latin vocabulum, meaning "a word, name." It forms an essential component of language and communication, helping convey thoughts, ideas, emotions, and information. Vocabulary can be oral, written, or signed and can be categorized into two main types: active vocabulary (words one uses regularly) and passive vocabulary (words one recognizes but doesn't use often). An individual's vocabulary continually evolves through various methods, including direct instruction, independent reading, and natural language exposure, but it can also shrink due to forgetting, trauma, or disease. Furthermore, vocabulary is a significant focus of study across various disciplines, like linguistics, education, psychology, and artificial intelligence. Vocabulary is not limited to single words; it also encompasses multi-word units known as collocatio

Topics in Educational Cyber-Physical Labs

Wissam Halimi

Recent advances in remote sensing and actuation technologies, coupled with the large reach of the internet, allowed for the emergence of applications such as cyber-physical labs. Cyber-physical labs are the digital and remotely-accessible equivalent of the lab equipment students use in school to experiment, through web-based interfaces such as web applications. Students, teachers and lab owners derive value from these systems, they are our stakeholders. Students are the intended users, teachers are the educational content curators and lab owners are the service providers. In this thesis, we take a close look at issues pertaining to cyber-physical labs and propose new approaches to address them. We also analyze the use of such systems in a MOOC, to detect the impact of the exherted experimental behavior of students on their academic performance. First, we tackle the case of the generation of web apps interfacing cyber-physical labs. It is the equivalent of preparing experiments for teachers by arranging the equipment for multiple experiments with the same equipment. We propose an extension to the Smart Device Specification for cyber-phyiscal labs, and a tool which generates these apps based on it. The automatically generated apps implement the necessary functions to use a cyber-physical lab, and are ready to be integrated in online learning platfroms. Next, we investigate issues related to the collection and retrieval of students' generated data through their interaction with cyber-physical labs. We consider the needs of students and lab owners. Through questionnaires sent to both parties, we elicit the requirements for an activity-tracking infrastructure composed of a vocabulary and an architectural model. The proposed vocabulary ensures deriving value from the recorded activity, and the proposed architecture addresses privacy and data access issues pertaining to students and lab owners respectively. We evaluate our proposal with two example cyber-physical labs. Last, we collect the interaction data with a cyber-physical lab used in a MOOC. We devise computational analyses on the students activity statistics, in search for indicators of academic performance. We find that high and low performing students show statistically different activity statistics. Then, we sequence the steps students did in an experiment, and don't find any statistically significant patterns for low and high-performing students. This analysis provides insights on the usage of installed facilities to service a potential massive access to limited resources (lab installations), and shed light on possible indicators for academic performance.

EPFL2018

Late Fusion of the Available Lexicon and Raw Waveform-based Acoustic Modeling for Depression and Dementia Recognition

Subrahmanya Pavankumar Dubagunta, Julian David Fritsch, Mathew Magimai Doss, Petr Motlicek

Mental disorders, e.g. depression and dementia, are categorized as priority conditions according to the World Health Organization (WHO). When diagnosing, psychologists employ structured questionnaires/interviews, and different cognitive tests. Although accurate, there is an increasing necessity of developing digital mental health support technologies to alleviate the burden faced by professionals. In this paper, we propose a multi-modal approach for modeling the communication process employed by patients being part of a clinical interview or a cognitive test. The language-based modality, inspired by the Lexical Availability (LA) theory from psycho-linguistics, identifies the most accessible vocabulary of the interviewed subject and use it as features in a classification process. The acoustic-based modality is processed by a Convolutional Neural Network (CNN) trained on signals of speech that predominantly contained voice source characteristics. In the end, a late fusion technique, based on majority voting, assigns the final classification. Results show the complementarity of both modalities, reaching an overall Macro-F1 of 84% and 90% for Depression and Alzheimer's dementia respectively.

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Topics in Educational Cyber-Physical Labs

Wissam Halimi

EPFL2018

A Modular System for the Harmonic Analysis of Musical Scores using a Large Vocabulary

Topics in Educational Cyber-Physical Labs

Late Fusion of the Available Lexicon and Raw Waveform-based Acoustic Modeling for Depression and Dementia Recognition

Topics in Educational Cyber-Physical Labs

Late Fusion of the Available Lexicon and Raw Waveform-based Acoustic Modeling for Depression and Dementia Recognition

A Modular System for the Harmonic Analysis of Musical Scores using a Large Vocabulary