Year: 2023
Type: preprint
Abstract: It has recently become feasible to run personal digital assistants on phones and other personal devices. In this paper we describe a design for a natural language understanding system that runs on device. In comparison to a server-based assistant, this system is more private, more reliable, faster, more expressive, and more accurate. We describe what led to key choices about architecture and technologies. For example, some approaches in the dialog systems literature are difficult to maintain over time in a deployment setting. We hope that sharing learnings from our practical experiences may help inform future work in the research community.
Source: arXiv (Cornell University)
Authors: Aas, Cecilia, Abdelsalam, Hisham, Belousova, Irina, Bhargava, Shruti, Cheng, Jianpeng, Daland, Robert, Driesen, Joris, Flego, Federico, Guigue, Tristan, Johannsen, Anders, Lal, Partha, Lu, Jiarui, Moniz, Joel Ruben Antony, Perkins, Nathan, Piraviperumal, Dhivya, Pulman, Stephen, Séaghdha, Diarmuid Ó, Sun, David Q., Torr, John, Del Vecchio, Marco, Wacker, Jay, Williams, Jason D., Yu, Hong
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4385714538