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Found 4 papers, 4 papers with code
Efficient keyword spotting using dilated convolutions and gating
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 using internal states.
Spoken Language Understanding on the Edge
We consider the problem of performing Spoken Language Understanding (SLU) on small devices typical of IoT applications.
Ranked #4 on
Spoken Language Understanding
on Snips-SmartSpeaker
Federated Learning for Keyword Spotting
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.
Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces
This paper presents the machine learning architecture of the Snips Voice Platform, a software solution to perform Spoken Language Understanding on microprocessors typical of IoT devices.
Ranked #52 on
Speech Recognition
on LibriSpeech test-other
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
