title: Turbocharge Speech Understanding with Pilot Inference
abstract: Modern speech understanding (SU) runs a sophisticated pipeline: ingesting streaming voice input, the pipeline executes encoder-decoder based deep neural networks repeatedly; by doing so, the pipeline generates tentative outputs (called hypotheses), and periodically scores the hypotheses. This paper sets to accelerate SU on resource-constrained edge devices. It takes a hybrid approach: to speed up on-device execution; to offload inputs that are beyond the device's capacity. While the approach is 
journal: arXiv (Cornell University)