The ultimate aim of the “Digital Primer” (DP) project is development, optimization and deployment of digital education instrument (Bildunginstrument) for fostering of acquisition of basic literacy in primary school pupils. DP has two sub-projects:

a “physical” Personal Primer (π2) branch focuses on design of a post-smartphone open hardware artefact based on “Raspberry Pi Zero” technology.

the “Web Primer” sub-project provides extended functionality in browser

Both sub-projects provide audiotext support, implement human-machine peer learning curricula and use Mozilla’s DeepSpeech acoustic models embelished with our own exercise-specific language models.

During this tutorial, participants will be introduced to diverse ways how speech-to-text (STT) inferences can be realized on non-cloud, local (i.e. edge-computing) architectures. Participants will acquire knowledge and competence concerning intricacies and nuances of execution of two different types of ASR systems (DeepSpeech and Random Forests) on three different hardware architectures (e.g. RaspberryPiZero (armv6); RaspberryPi 4 (armv7 without CUDA) and NVIDIA Jetson Xavier (armv8 / aarch64 with CUDA). Thus, in 90 minutes of a hands-on tutorial participants will acquire practical know-how about how to transform all three hardware platforms into a low-cost local STT inference engine.