AuthorsCecilia Aas, Hisham Abdelsalam, Irina Belousova, Shruti Bhargava, Jianpeng Cheng, Robert Daland, Joris Driesen, Federico Flego, Tristan Guigue, Anders Johannsen, Partha Lal, Jiarui Lu, Joel Ruben Antony Moniz, Nathan Perkins, Dhivya Piraviperumal, Stephen Pulman, Diarmuid Ó Séaghdha, David Q. Sun, John Torr, Marco Del Vecchio, Jay Wacker, Jason D. Williams, Hong Yu
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.
Earlier this year, Apple hosted the Natural Language Understanding workshop. This two-day hybrid event brought together Apple and members of the academic research community for talks and discussions on the state of the art in natural language understanding.
In this post, we share highlights from workshop discussions and recordings of select workshop talks.
Apple attended Interspeech 2019, the world's largest conference on the science and technology of spoken language processing. The conference took place in Graz, Austria from September 15th to 19th. See accepted papers below.
Apple continues to build cutting-edge technology in the space of machine hearing, speech recognition, natural language processing, machine translation, text-to-speech, and artificial intelligence, improving the lives of millions of customers every day.
Our research in machine learning breaks new ground every day.