116 citations · 116 across the 1 of their papers we have counts for
4 papers
Noisy student-teacher training for robust keyword spotting
Hyun-Jin Park, Pai Zhu, Ignacio Lopez Moreno +1
We propose self-training with noisy student-teacher approach for streaming keyword spotting, that can utilize large-scale unlabeled data and aggressive data augmentation. The propo…
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…
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…
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…