학술논문

Spoken Language Understanding on the Edge
Document Type
Conference
Source
2019 Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing - NeurIPS Edition (EMC2-NIPS) EMC2-NIPS Energy Efficient Machine Learning and Cognitive Computing - NeurIPS Edition (EMC2-NIPS), 2019 Fifth Workshop on. :57-61 Dec, 2019
Subject
Computing and Processing
Performance evaluation
Privacy
Microcontrollers
Machine learning
Reproducibility of results
Real-time systems
Energy efficiency
spoken language understanding
speech recognition
privacy
embedded inference
Language
Abstract
We consider the problem of performing Spoken Language Understanding (SLU) on small devices typical of IoT applications. Our contribution is two-fold. First, we outline the design of an embedded, private-by-design SLU system and show that it has performance on-par with cloud-based commercial solutions. Second, we release the datasets used in our experiments in the interest of reproducibility and in the hope that they can prove useful to the community.