7 citations · 7 across the 1 of their papers we have counts for
8 papers
A study on more realistic room simulation for far-field keyword spotting
Eric Bezzam, Robin Scheibler, Cyril Cadoux +1
We investigate the impact of more realistic room simulation for training far-field keyword spotting systems without fine-tuning on in-domain data. To this end, we study the impact…
Small-Footprint Open-Vocabulary Keyword Spotting with Quantized LSTM Networks
Théodore Bluche, Maël Primet, Thibault Gisselbrecht
We explore a keyword-based spoken language understanding system, in which the intent of the user can directly be derived from the detection of a sequence of keywords in the query.…
Predicting detection filters for small footprint open-vocabulary keyword spotting
Theodore Bluche, Thibault Gisselbrecht
In this paper, we propose a fully-neural approach to open-vocabulary keyword spotting, that allows the users to include a customizable voice interface to their device and that does…
Efficient keyword spotting using dilated convolutions and gating
Alice Coucke, Mohammed Chlieh, Thibault Gisselbrecht +3
We explore the application of end-to-end stateless temporal modeling to small-footprint keyword spotting as opposed to recurrent networks that model long-term temporal dependencies…
Spoken Language Understanding on the Edge
Alaa Saade, Alice Coucke, Alexandre Caulier +9
We consider the problem of performing Spoken Language Understanding (SLU) on small devices typical of IoT applications. Our contributions are twofold. First, we outline the design…
Federated Learning for Keyword Spotting
David Leroy, Alice Coucke, Thibaut Lavril +2
We propose a practical approach based on federated learning to solve out-of-domain issues with continuously running embedded speech-based models such as wake word detectors. We con…