Jaco: An Offline Running Privacy-aware Voice Assistant
Daniel Bermuth, Alexander Poeppel, Wolfgang Reif

TL;DR
Jaco is a privacy-aware, offline-capable voice assistant designed for low-resource devices, offering extensibility, multi-language support, and competitive performance while prioritizing user privacy.
Contribution
It introduces a novel offline voice assistant architecture that balances privacy, extensibility, and multi-language support on low-resource devices.
Findings
Operates effectively on RaspberryPi and similar devices
Maintains user privacy without sacrificing capabilities
Achieves competitive performance with existing solutions
Abstract
With the recent advance in speech technology, smart voice assistants have been improved and are now used by many people. But often these assistants are running online as a cloud service and are not always known for a good protection of users' privacy. This paper presents the architecture of a novel voice assistant, called Jaco, with the following features: (a) It can run completely offline, even on low resource devices like a RaspberryPi. (b) Through a skill concept it can be easily extended. (c) The architectural focus is on protecting users' privacy, but without restricting capabilities for developers. (d) It supports multiple languages. (e) It is competitive with other voice assistant solutions. In this respect the assistant combines and extends the advantages of other approaches.
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Taxonomy
TopicsAI in Service Interactions · Context-Aware Activity Recognition Systems · IoT and Edge/Fog Computing
