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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.

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Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

We describe the design of our federated task processing system. Originally, the system was created to support two specific federated tasks: evaluation and tuning of on-device ML systems, primarily for the purpose of personalizing these systems. In recent years, support for an additional federated task has been added: federated learning (FL) of deep neural networks. To our knowledge, only one other system has been described in literature that…
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Interspeech 2019

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.

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