Open Virtual Assistant Manifesto
Democratize AI for linguistic user interfaces. We should have open, collaborative research to put open-source linguistic technology in the hands of all businesses. (The LUInet project)
An open non-proprietary linguistic web. All skills, or linguistic user interfaces, should be made available to any virtual assistant. (The Thingpedia project)
Sharing with individual data ownership. Consumers should have a choice in virtual assistant services and the ability to control how we share our data. (The Almond project)
We are starting a world-wide open-source initiative, Open Virtual Assistant Lab (OVAL), to create an ecosystem founded on open virtual assistant technology.
OVAL is supported by the National Science Foundation under Grant No. 1900638.
This project gathers together experts in distributed systems, programming languages, natural language processing, machine learning, knowledge engineering, security, human-computer interaction, and crowdsourcing to create the world’s best virtual assistant.
Presentations & Interviews
- "Stanford Team Aims at Alexa and Siri With a Privacy-Minded Alternative", John Markoff for the New York Times, 6/14/2019
- "Privacy in the age of virtual assistants", Russ Altman for the Future of Everything (podcast), 6/4/2019
- "Giving Control Back to Consumers with Open Federated Virtual Assistants", Monica Lam, Keynote at HiPEAC 2019, 1/21/2019
- "Keeping the Internet Open with an Open-Source Virtual Assistant", Monica Lam, Keynote at Mobicom 2018, 11/1/2018
Almond is a general-purpose, federated virtual assistant that respects the user's
privacy by running on-device and offering flexible access control.
An open, crowdsourced repository of Web and Internet of Things APIs, their metadata and
all the ways to express them in natural language.
An open-source dataset and model for natural language understanding in virtual
assistants, as well as tools to acquire data and extend it to new domains.
Brassau combines voice with automatically generated graphical user interfaces
to take advantage of the best of each modality.
Controlling Fine-Grain Sharing in Natural Language with a Virtual Assistant
Giovanni Campagna, Silei Xu, Rakesh Ramesh, Michael Fischer, and Monica S. Lam
In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2018.
Brassau: Automatically Generating Graphical User Interfaces for Virtual Assistants
Michael Fischer, Giovanni Campagna, Silei Xu, and Monica S. Lam
In 20th International Conference on Human-Computer Interaction with Mobile Devices and Services. (MobileHCI), 2018.
Almond: The Architecture of an Open, Crowdsourced, Privacy-Preserving, Programmable Virtual Assistant
Giovanni Campagna, Rakesh Ramesh, Silei Xu, Michael Fischer, and Monica S. Lam
In Proceedings of the 26th International World Wide Web Conference (WWW), Perth, Australia, April 2017.
Previous members of our team include Albert Chen, Zhiyang He, Jiaqi Xue, Aashna Garg, Jiwon Seo, Sadjad Fouladi, Reynis Vazquez, Rakesh Ramesh. We thank them for their valuable contribution.