3 papers
eess.AS2020
Training Keyword Spotting Models on Non-IID Data with Federated Learning
Andrew Hard, Kurt Partridge, Cameron Nguyen +5
We demonstrate that a production-quality keyword-spotting model can be trained on-device using federated learning and achieve comparable false accept and false reject rates to a ce…
eess.AS2020
Streaming keyword spotting on mobile devices
Oleg Rybakov, Natasha Kononenko, Niranjan Subrahmanya +2
In this work we explore the latency and accuracy of keyword spotting (KWS) models in streaming and non-streaming modes on mobile phones. NN model conversion from non-streaming mode…
cs.CL2020
Learning To Detect Keyword Parts And Whole By Smoothed Max Pooling
Hyun-Jin Park, Patrick Violette, Niranjan Subrahmanya
We propose smoothed max pooling loss and its application to keyword spotting systems. The proposed approach jointly trains an encoder (to detect keyword parts) and a decoder (to de…