Christian D. Vázquez

TagAlong: Informal Learning from a Remote Companion with Mobile Perspective Sharing

12th International Conference CELDA 2015

Questions often arise spontaneously in a curious mind, due to an observation about a new or unknown environment.When an expert is right there, prepared to engage in dialog, this curiosity can be harnessed and converted into highly effective, intrinsically motivated learning. This paper investigates how this kind of situated informal learning can be realized in real-world settings with wearable technologies and the support of a remote learning companion.

TakeTwo: Using Google Glass for Augmented Memory

CHI Video Showcase 2015

Recent advances in wearable technology create the opportunity for seamless interactions that would be too cumbersome or limited on handheld devices such as cameras or mobile phones. When presented with large amounts of information, people are prone to miss or forget details which can be essential later. TakeTwo builds on the capabilities of wearable devices to provide a virtual extension of memory, i.e. augmented memory, to aid users in learning and recall.

Serendipitous Language Learning in Mixed Reality

CHI Late Breaking Work 2017

Mixed Reality promises a new way to learn in the world: blending holograms with our surroundings to create contextually rich experiences that find their place in our daily routine. Existing situated learning platforms limit the learner and implicitly enforce the designer’s intent by hard-coding content and predetermining what elements in the environment are actionable. In this paper, we define the framework of Serendipitous Learning in Mixed Reality as situated, incidental learning that occurs naturally in the user’s environment and stems from the learner’s curiosity. This framework is explored within the context of second language acquisition.

I-vector speaker and language recognition system on Android

IEEE HPEC 2016

I-Vector based speaker and language identification provides state of the art performance. However, this comes as a more computationally complex solution, which can often lead to challenges in resource-limited devices, such as phones or tablets. We present the implementation of an I-Vector speaker and language recognition system on the Android platform in the form of a fully functional application that allows speaker enrollment and language/speaker scoring within mobile contexts. We include a detailed account of the challenges to port the system and its dependencies, which were necessary to optimize matrix operations in the I-Vector implementation.